US20090307263A1 - System And Method Of Performing Location Analytics - Google Patents
System And Method Of Performing Location Analytics Download PDFInfo
- Publication number
- US20090307263A1 US20090307263A1 US12/134,634 US13463408A US2009307263A1 US 20090307263 A1 US20090307263 A1 US 20090307263A1 US 13463408 A US13463408 A US 13463408A US 2009307263 A1 US2009307263 A1 US 2009307263A1
- Authority
- US
- United States
- Prior art keywords
- individualized
- implemented method
- computer implemented
- data point
- location
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3476—Special cost functions, i.e. other than distance or default speed limit of road segments using point of interest [POI] information, e.g. a route passing visible POIs
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3626—Details of the output of route guidance instructions
- G01C21/3641—Personalized guidance, e.g. limited guidance on previously travelled routes
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3679—Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3679—Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities
- G01C21/3682—Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities output of POI information on a road map
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/16—Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0261—Targeted advertisements based on user location
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/01—Social networking
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/0969—Systems involving transmission of navigation instructions to the vehicle having a display in the form of a map
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72448—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions
- H04M1/72457—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions according to geographic location
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M11/00—Telephonic communication systems specially adapted for combination with other electrical systems
- H04M11/04—Telephonic communication systems specially adapted for combination with other electrical systems with alarm systems, e.g. fire, police or burglar alarm systems
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
- H04N21/4508—Management of client data or end-user data
- H04N21/4524—Management of client data or end-user data involving the geographical location of the client
Definitions
- the present invention generally relates to systems and methods for performing sensor analytics. More specifically, the present invention relates to systems and methods for associating time/location data points.
- location-based media delivers multimedia directly to the user of a mobile device dependent upon their location
- the media can be delivered to, or triggered within any portable wireless device that is location enabled and has the capacity to display audiovisual content.
- Media content is managed and organized externally of the device on a standard desktop or laptop.
- the mobile device then downloads formatted content with location coordinated triggers applied to each media sequence.
- the assigned media is triggered.
- the assigned media is designed to be of optimal relevance to the user in the context of the user's surroundings.
- the present invention generally relates to systems and methods for performing sensor analytics. More specifically, the present invention relates to systems and methods for associating time/location data points.
- a location source having a unique identifier can be associated with a time, a place, or a time and place.
- One or more demographic profiles can be associated with the time and or place. Multiple time, place and associated demographic profiles can result in the determination of a likely profile of the unique identifier. The geographic location of the unique identifier with the profile association can then be displayed in real time with other unique identifiers with the same or different profile associations.
- a computer implemented method for conveying aggregate location based information comprising: receiving one or more individualized data points; associating one or more demographics profiles with the individualized data point; aggregating the individualized data point and associated demographic with a second location data point having a second associated demographic profile; and exporting the aggregate location data.
- the received individualized data is associated with an individual user, an individual location enabled device, a mobile device, or anonymously associated with a specific user or device.
- the individualized data point can be associated with at least one user and received from a data provider or data aggregator.
- the individualized data can be received in real time or according to a predetermined schedule.
- the individualized data can be received according to a source profile.
- the individualized data points can be associated with a historical file.
- the individualized data point can be associated with a demographic profile wherein the demographic profile comprises historical location data points.
- the demographic profile can comprise information from the group comprising: Census Bureau data, financial demographics, social demographics, tribe/group demographics, historical demographical information; derived demographic information; gender; race; educational level; historical geographic information; or user entered information/preferences.
- a demographic profile can be disassociated from an individualized data point or a profile.
- a demographic profile can be selectively disassociated from an individualized data point or profile.
- Historical demographics can be disassociated from an individualized data point or profile. Historical demographics can be selectively disassociated from an individualized data point or profile.
- an individualized data point and associated demographic can be associated with a second individualized data point and second associated demographic, wherein the individualized data point and second data point are related to the same user or to different users.
- multiple individualized data points can be aggregated to derive one or more tribes relating to the individualized data points or associated demographics. Having determined a tribal affiliation of the individualized data points, a further implementation can recommend items of interest associated with a tribe. Items of interest can be recommended based on a historical record of an individualized data point. The individualized data point can be identified with all tribes of interest to the individualized data point. Tribal activity can be indexed based on tribal historical location data.
- a plurality of individualized data points associated and aggregated with a tribe are exported to a display on a user interface.
- the display can include a map of an area of interest.
- the display can be in real time. Tribes can be selectively displayed on a map of an area of interest. Items of interest associated with a tribe can be displayed on a map of an area of interest. Items of interest associated with a tribe can be listed in a textual document or in a list view.
- a computer readable medium wherein the computer readable medium has stored thereon a computer program that, when executed, causes a computer to perform the steps of: receiving one or more individualized data points; associating one or more demographics profiles with the individualized data point; aggregating the individualized data point and associated demographic with a second location data point having a second associated demographic profile; and exporting the aggregated individualized data point and second location data point.
- a system for determining and conveying aggregate location based information comprising: a network; one or more location enabled user devices in communication with the network, wherein the one or more location enabled user devices have an individualized location data point, and a processor in communication with the network, wherein the processor receives one or more individualized location data points from the one or more location enabled user devices, the processor associates the one or more individualized location data points with one or more demographic profiles and aggregates the individualized location data point having the associated demographic profile with a second location data point having a second associated demographic profile, and exports the aggregated individualized location data point and the second location data point to the network.
- FIG. 1 shows a series of screen shots depicting the location of associated data in accordance with an implementation of the present invention
- FIG. 2 shows a flow chart of an implementation of the present invention
- FIG. 3 shows a screen shot depicting associated data in accordance with an implementation of the present invention
- FIG. 4 shows a screen shot for managing associated data in accordance with the present invention
- FIG. 5 shows a screen shot for managing associated data in accordance with the present invention
- FIG. 6 shows a screen shot depicting associated data in accordance with the present invention
- FIG. 7 shows a screen shot for managing associated data in accordance with the present invention.
- FIG. 8 shows a screen shot depicting associated data in accordance with the present invention.
- FIG. 9 shows a system diagram of an implementation of the present invention
- the present invention generally relates to systems and methods for performing sensor analytics. More specifically, the present invention relates to systems and methods for associating time/location data points.
- a location source having a unique identifier can be associated with a time, a place, or a time and place.
- One or more demographic profiles can be associated with the time and or place. Multiple time, place and associated demographic profiles can result in the determination of a likely user profile of the unique identifier. The geographic location of the unique identifier with the profile association can then be displayed in real time with other unique identifiers with the same or different profile associations.
- the time and place of the unique identifier can be associated with one or more demographic profiles, for example, census bureau data.
- one or more demographic profiles for example, census bureau data.
- certain inferences can be made about the unique identifier.
- a cellular telephone that is frequently in the warehouse district of city “Metropolis” during normal business hours can be associated with the transportation or logistics business sector.
- a cellular telephone that is frequently in the warehouse district of city “Metropolis” during the late night and early morning hours can be associated with the late night entertainment industry.
- the cellular telephone that is in the warehouse district during business hours may also be found in suburban retail locations during the early evening hours and in a middle-class suburban neighborhood during the late night and early morning hours.
- the user of the first cellular telephone can be assigned a source profile.
- the user of the first cellular telephone can generally be associated with groups identifying with middle-class working people leading a largely suburban lifestyle.
- the second cellular telephone may also be found in and around a university campus during business hours and frequently located in a lower rent neighborhood having a high percentage of students during overnight hours. From the demographic data associated with the historical record of the second cellular telephone's time and location data, the user of the second telephone can generally be associated with groups identifying with socially active college or graduate students.
- first cellular telephone and the second cellular telephone meaningful information in the form of a user or source profile was determined by linking or associating various demographic or other information with the times and places that the various location sources, and by extension the user, traveled.
- the user or source profile was determined without the benefit of a prior registered profile of the user, or without soliciting profiling information such as user or consumer preferences.
- the user or source profile was determined without the user choosing which demographic, consumer or user groups he or she would prefer to be associated with. As such, the groups or “tribes” that the user is likely to identify with are an accurate reflection of the user's habits or actual behavior.
- a “tribe” is any association of a unique identifier with other unique identifiers that share a common demographic profile or other common association. Tribes can include individuals that are in a particular place at a particular time or individuals that frequent a particular place during a particular occurrence. For example, and without limitation, a tribe can include all individuals that visit a shopping mall on Saturday afternoon or all individuals that visit a shopping mall during a sale or discount event.
- a tribe can include an association of individuals, devices or other unique identifiers by age, gender, race, religion, national or regional origin, organizational membership or participation, educational level, income level, tax bracket, profession, vocation, occupation, consumer demographical information, political leaning, hobby, interest, activity, geographic location, neighborhood, town, borough, city, county, state, preferred consumer/retail/wholesale provider, event, occurrence, participation in an event or occurrence, time or time period, or any other shared experience in type, time or location between two or more unique identifiers.
- a “unique identifier” is any information that identifies a particular person, device, object, event or place at a particular time, occurrence or location.
- a unique identifier can be a location enable device, such as a cellular telephone, a GPS enabled device, a networked device, a WiFi enabled device, an RFID enabled device, an ATM machine, or any other device that identifies a time/location data point.
- a unique identifier can also include a place or event that identifies a time/location data point associated with that place or event.
- a “time/location data point” is data or other information that identifies a specific event, user, or device at a specific time and/or location.
- a time/location data point can include: a time stamp associated with a geographic location, such as, the time at a latitude and longitude; a time stamp associated with a specific event at a fixed geographic location, such as, the time of a special or sale at a store or entertainment venue; or the occurrence of an event at a particular time and location, such as, a full taxi cab in the warehouse district at 2:00 am.
- an “individualized location data point” is a unique identifier having a time/location data point.
- An individualized location data point can be associated with one or more tribes.
- one or more individualized data points associated with one or more tribes are displayed on a map.
- the display is in real time.
- the display is delayed from real time by a time differential.
- the display is refreshed according to a predetermined schedule. [predicting the future]
- the relative population density of individualized data points comprising a tribe in any given location is displayed.
- places and events of interest are displayed that are of interest to the tribes displayed.
- targeted information is displayed with the geographic location and population density of a tribe.
- tribe membership of an individualized data point is determined based on historical location and time data. In an implementation tribe membership is determined based on demographic information associated with the time/location data point associated with the individualize data point. In an implementation demographic profiles of one or more individualized data points are derived from tribe membership, time/location data points, demographic information associated with time/location data points, historical data associated and unassociated with a time/location data point, or historical data associated and unassociated with an individualized data point.
- demographic information and “demographic profile” means any information, historical or derived, which describes or categorizes a particular place, location, event, occurrence, time or period of time, individual, user, device or object, unique identifier, and the like.
- Demographic information and demographic profile can include, without limitation: Census Bureau data, age, gender, religion, ethnicity, national or regional origin, education level, income level, employment, occupation, vocation, career, hobby, interest, marital status, sexual orientation, consumer preferences, consumer habits, organizational membership and participation, occurrence of an event, geographic location, time or time period, tribe membership and/or tribe association.
- mobile device 10 includes a user interface having a display 11 on which one or more tribes can be displayed at various geographic locations, such as locations on a city map, at a particular point in time.
- tribes 14 and 16 are displayed at various locations around City X, including neighborhood 18 and neighborhood 20 , at time 12:00:00.
- In view 13 tribes 14 and 16 are displayed at various locations around City X, including neighborhood 18 and neighborhood 20 at time 00:00:00.
- Tribes can be identified on the display 11 by tribe indicators 14 and 16 .
- Tribe indicators 14 and 16 can be of any unique icon, shape or color that distinguishes one tribe from another.
- tribe 14 clusters around location 22 in neighborhood 18 at time 12:00:00. Tribe 14 is also fairly dispersed between neighborhoods 18 and 20 at time 00:00:00. Also, tribe 16 is fairly dispersed between neighborhoods 18 and 20 at time 12:00:00 and concentrated at location 24 and 26 in neighborhood 20 at time 00:00:00.
- knowing demographic information about neighborhoods 18 and 20 , as well as locations 22 , 24 , and 26 can provide meaningful information leading to a user profile for members of tribes 14 and 16 .
- FIG. 2 depicts an exemplary method 200 for associating information with a time/location data point to determine, for example tribe membership, including receiving individualized time/location data points 210 ; associating the individualized time/location data points with demographic information 220 and associating the individualized time/location data point with a historical record the unique identifier associated with the individualized time/location data point 230 ; deriving source profiles, demographic profiles and/or demographic information associated with the individualized time/location data point 240 ; aggregating two or more individualized time/location data points having associated source or demographic profiles 250 ; and displaying the aggregated individualized time/location data points 260 .
- individualized time/location data is received, for example, at a location based service provider facility.
- an individualized time/location data point is data or other information that identifies a specific event, user, or device at a specific time and/or location.
- This can include GPS data from a specific GPS enables device, such as a GPS enabled cellular telephone, navigational device, laptop computer, and the like.
- This can also include the location of a cellular telephone within the cellular network, i.e., the location of the particular cellular telephone within a particular cell at a particular time.
- This can also include passive location based services such as ATM machines, which give the time and location of a unique user.
- the individualized time/location data point is unique to the source of the data, for example, unique to the cellular telephone, ATM debit card, or EZPass RFID transmitter.
- demographic information can be associated with the time, place or time and place for which the unique source is located.
- demographic information and profiles are associated 220 with the individualized time/location data point.
- the demographic information can identify, for example the average income, age, and educational level of residents living in the neighborhood for which the unique identifier is located, as indicated by the individualized time/location data point.
- the demographic information can include, for example, the consumer trends and profiles associated with individuals who have previously been at the location during the time that the unique identifier also located, as indicated by the individualized time/location data point.
- the demographic information that can be associated with the time and/or location can include a variety of information including: Census Bureau data, age, gender, religion, ethnicity, national or regional origin, education level, income level, employment, occupation, vocation, career, hobby, interest, marital status, sexual orientation, consumer preferences, consumer habits, organizational membership and participation, occurrence of an event, geographic location, time or time period, tribe membership and/or tribe association.
- a historical record of the previous locations to which the unique identifier has traveled can also be analyzed and associated 230 with the individualized time/location data point. For example, based on previous locations that the unique identifier has traveled, various tribes may already be attributed to the unique identifier. Additionally, various demographic profiles associated with the previous locations of the unique identifier may also be known. By way of example, a unique identifier that spends four hours every afternoon in an exclusive shopping district can be associated with a number of demographics and/or tribes. But knowing that the same unique identifier spent the previous four hours at a community college in a largely immigrant community adds additional information leading to a smaller set of likely tribal associations.
- Derivation 240 of the associated demographic profiles can include comparing the individualized time/location data point and previous or historical tribal associations with demographic information related to the location and time of the current position of the unique identifier. Derivation 240 allows for further refinement of tribal associations and assignment of new tribal associations. Derived analytics can be obtained. Such analytics include, without limitation, a relative degree of association of the unique identifier with a tribe and or recommendations of places, topics, events or items of interest to a particular tribe.
- Derivation 240 allows for linking and storing 245 of demographic information with the unique identifier for future use in historical association 230 as more individualized time/location data points become available.
- the stored demographic information can be exported to other applications for further analysis.
- a plurality of individualized time/location data points having tribal associations are aggregated 250 to determine the location of members of any particular tribe.
- Analytics can be performed on the aggregated data, including: population density of tribes within a given geographic location, such as the number of middle income individuals over 30 at a shopping mall; the number of tribal members within one or more designated areas at a designated time or time period, such as the number of women under 25 at specific retail locations during a sales event; and the occurrence of an event for a tribal member in a specific location at a specific time, such as the number of a taxi cabs carrying passengers in the late afternoon in the financial district of a city.
- Display 260 of the aggregated derived tribal information can be, for example, to a mobile device, a user terminal such as a personal computer, a networked system display such as an ATM, or a public display.
- the mobile device 310 includes display 311 having display view 312 showing the location of tribes 314 and 316 at various locations in City X including neighborhood 318 and 320 . Relying on analytics performed on the aggregated individualize time/location data points, as described above, population density for a particular tribe is shown by varying the size of the tribal icon 314 .
- tribal icon 315 is similar to but smaller than tribal icon 314 , thereby indicating fewer tribal members at the location indicated by tribal icon 315 .
- tribal icon is similar to but larger than tribal icon 316 , thereby indicated more tribal members at the location indicated by tribal icon 317 .
- the relative population density of a tribe can be indicated by any manner of display means including variations in icon size, shape, color, intensity, and the like.
- information relating to tribes, tribe location, tribal population density and the like can be conveyed to the user in graphical or textual format, for example, as icons on a map view or as a list view in a textual document.
- a user interface is provided on a mobile device 410 having a display 411 .
- View 412 of display 411 shows a user tribal associations to which the user belongs.
- tribal associations are determined by associating the unique identifier of the particular mobile device of the user with a particular place at a particular time to obtain an individualized time/location data point. Demographic and historical information are associated with the individualized data point and the unique identifier to derive certain tribal associations.
- View 412 displays to the user two tribal associations 420 and 422 along with certain derived information, such as, for example, the percentage of association of the user with Tribe A indicated by percentage display 421 and 423 .
- the user can access additional derived information through user prompt 424 and 425 , such as, for example, obtaining information about items of interest to a particular tribe.
- View 413 depicts additional derived information available to the user, such as for example, recommended items of interest for a particular tribe.
- the recommended items of interest can include retail locations, services, organizations, places of interest, people of interest, tribes of interest, events and the like.
- view 413 shows that members of Tribe A are also interested in Tribe C.
- the user can be prompted to obtain more information about the recommended item of interest, as in prompt 430 or to participate in the item of interest, as in prompt 432 .
- FIG. 5 depicts another exemplary implementation of a user interface for gaining access to derived information associated with a tribe. For example, the user can be prompted to obtain items of interest to tribe A through user prompt 515 .
- FIG. 6 depicts an exemplary implementation of view 612 showing an item of interest at a location 640 having a relatively high population density of members of tribe A.
- Call out 660 can be an interactive window or other user prompt allowing connectivity via the internet, telephone line, email, text message or other media to the item of interest at the location 640 .
- FIG. 7 depicts an exemplary user interface for managing a user profile associated with a unique identifier and associated demographic and historical information.
- View 712 of display 710 shows user prompts 750 for view tribes to which the user may be assigned, user prompt 752 for refreshing or deleting the source profile, account management prompt 754 and other miscellaneous prompts 756 .
- FIG. 8 depicts an exemplary user display 711 including view 712 showing advertising information 730 displayed in a window or banner.
- Advertising information 712 can include any information likely to be of interest to a tribe to which the user belongs or targeted to the user based on tribal affiliation, information in the source profile including associated demographic and historical information, geographic location of the unique identifier, and the like.
- the location of tribal members can be displayed on the user display of a mobile device at any time by deliberately shaking the device in a repeated manner.
- An accelerometer embedded within the mobile device sense the shaking of the device and instructs the device to display the current location of the tribal members.
- functionality of the user device such as a mobile telephone can be linked to derived information available to the user.
- the alarm function of the mobile telephone can be triggered should the population density of a tribe at a particular location reach a predetermined number.
- An example can include an alarm trigger if the number of vehicles passing over a bridge or toll booth exceed X number per minute.
- FIG. 9 depicts a system diagram of an exemplary implementation.
- System 900 includes system server 910 .
- System server 910 can include a processor coupled to a computer readable memory.
- System server is in communication with individualized time/location data point historical file 914 and source profile 916 .
- Historical file 914 and source profile 916 can be stored on system server 910 or on a secondary storage device (not shown).
- System server 910 is also in communication with database bank 920 .
- Database bank 920 can include one or more data bases or access to databases including Census Database 921 , Demographic information database 922 , Location database 923 , activity database 924 , and advertising database 925 . Other databases can be used.
- System server 910 and database bank 920 are in communication with Derived association engine 930 and aggregation engine 940 .
- System server 910 is also in communication with user device 950 , user terminal 960 and public display 970 via network 980 .
- Network 980 can be the Internet.
- System server 910 receives an individualized time/location data point from either user device 950 or user terminal 960 .
- the system server 910 is configured to associate the individualized time/location data point with a source profile 916 and a historical file 914 .
- Derived association engine 940 is configured to match demographic information retrieved from database bank 920 with the individualized time/location data point and associated historical information and assign one or more tribes to the individualized data point. The tribal association is recorded and the historical data file 914 and source file 916 are updated.
- Aggregation engine 940 is configured to compile individualized time/location data points with their associated tribal designations. Aggregation engine 940 is further configured to determine additional derived data relating to the number and frequency of various individualized data points and/or tribal members within a given place, location or time period. Aggregation engine 940 provides the aggregated location of all individualized data points within a tribe along with the additional derived data to system server 910 . System server 910 then exports the aggregated and derived data to user device 950 , user terminal 960 and public display 910 . The aggregate data can be exported in a data feed for further processing, or displayed on a user display or public display in graphical or tabulated form.
Abstract
A system and method are provided for associating location data from one or more unique sources. The place and time of a unique location enabled device are associated with stored demographic information relating to the particular place and particular time. The place and time of the unique location enabled device are associated with a historical record of past locations and time of locations that the device has been. Based on the association of demographical information and historical information, the unique location enable device is assigned to one or more groups or tribes. The location of all members of the group or tribe can be aggregated and exported for further analysis or display, thereby showing all group or tribe members at a particular time and place.
Description
- The present invention generally relates to systems and methods for performing sensor analytics. More specifically, the present invention relates to systems and methods for associating time/location data points.
- The proliferation of GPS and other positioning methods in mobile phones, taxis, personal navigation devices and automobiles has begun to generate an enormous amount of historic and real-time data, consisting of a latitude, longitude, unique identifier, and some metadata in many cases like if a taxi is full or empty.
- For example, location-based media (LBM) delivers multimedia directly to the user of a mobile device dependent upon their location The media can be delivered to, or triggered within any portable wireless device that is location enabled and has the capacity to display audiovisual content. Media content is managed and organized externally of the device on a standard desktop or laptop. The mobile device then downloads formatted content with location coordinated triggers applied to each media sequence. As the location-aware device enters the selected area, the assigned media is triggered. The assigned media is designed to be of optimal relevance to the user in the context of the user's surroundings.
- In addition to location based media, there are other back-end server systems that process sensor data in real-time, including GPS, Wifi, and other location data, for example, a taxi dispatch system, the air traffic control system, or RFID systems for tracking supply chains. All of these systems were built for a specific purpose, a specific kind of sensor, and provide limited and focused analysis relevant to the specialized system. Moreover, historical information and related geographic information is typically limited to the current time and place of the subject of interest.
- There has not been a system employing methodologies to associate data based on the historical location record of an individual device or user and demographic data that may be associated with the locations in the historical location record of an individual user.
- The present invention generally relates to systems and methods for performing sensor analytics. More specifically, the present invention relates to systems and methods for associating time/location data points. In an exemplary implementation, a location source having a unique identifier can be associated with a time, a place, or a time and place. One or more demographic profiles can be associated with the time and or place. Multiple time, place and associated demographic profiles can result in the determination of a likely profile of the unique identifier. The geographic location of the unique identifier with the profile association can then be displayed in real time with other unique identifiers with the same or different profile associations.
- In another implementation a computer implemented method is provided for conveying aggregate location based information comprising: receiving one or more individualized data points; associating one or more demographics profiles with the individualized data point; aggregating the individualized data point and associated demographic with a second location data point having a second associated demographic profile; and exporting the aggregate location data.
- In other implementations the received individualized data is associated with an individual user, an individual location enabled device, a mobile device, or anonymously associated with a specific user or device. The individualized data point can be associated with at least one user and received from a data provider or data aggregator. The individualized data can be received in real time or according to a predetermined schedule. The individualized data can be received according to a source profile. The individualized data points can be associated with a historical file.
- In yet another implementation associating the source profile with the individualized data point maintains the anonymity of the user. The individualized data point can be associated with a demographic profile wherein the demographic profile comprises historical location data points. The demographic profile can comprise information from the group comprising: Census Bureau data, financial demographics, social demographics, tribe/group demographics, historical demographical information; derived demographic information; gender; race; educational level; historical geographic information; or user entered information/preferences. A demographic profile can be disassociated from an individualized data point or a profile. A demographic profile can be selectively disassociated from an individualized data point or profile. Historical demographics can be disassociated from an individualized data point or profile. Historical demographics can be selectively disassociated from an individualized data point or profile.
- In still a further implementation, an individualized data point and associated demographic can be associated with a second individualized data point and second associated demographic, wherein the individualized data point and second data point are related to the same user or to different users.
- In another implementation, multiple individualized data points can be aggregated to derive one or more tribes relating to the individualized data points or associated demographics. Having determined a tribal affiliation of the individualized data points, a further implementation can recommend items of interest associated with a tribe. Items of interest can be recommended based on a historical record of an individualized data point. The individualized data point can be identified with all tribes of interest to the individualized data point. Tribal activity can be indexed based on tribal historical location data.
- In a further implementation a plurality of individualized data points associated and aggregated with a tribe are exported to a display on a user interface. The display can include a map of an area of interest. The display can be in real time. Tribes can be selectively displayed on a map of an area of interest. Items of interest associated with a tribe can be displayed on a map of an area of interest. Items of interest associated with a tribe can be listed in a textual document or in a list view.
- In another implementation a computer readable medium is provided wherein the computer readable medium has stored thereon a computer program that, when executed, causes a computer to perform the steps of: receiving one or more individualized data points; associating one or more demographics profiles with the individualized data point; aggregating the individualized data point and associated demographic with a second location data point having a second associated demographic profile; and exporting the aggregated individualized data point and second location data point.
- In yet another implementation a system for determining and conveying aggregate location based information is provided, the system comprising: a network; one or more location enabled user devices in communication with the network, wherein the one or more location enabled user devices have an individualized location data point, and a processor in communication with the network, wherein the processor receives one or more individualized location data points from the one or more location enabled user devices, the processor associates the one or more individualized location data points with one or more demographic profiles and aggregates the individualized location data point having the associated demographic profile with a second location data point having a second associated demographic profile, and exports the aggregated individualized location data point and the second location data point to the network.
-
FIG. 1 shows a series of screen shots depicting the location of associated data in accordance with an implementation of the present invention; -
FIG. 2 shows a flow chart of an implementation of the present invention; -
FIG. 3 shows a screen shot depicting associated data in accordance with an implementation of the present invention; -
FIG. 4 shows a screen shot for managing associated data in accordance with the present invention; -
FIG. 5 shows a screen shot for managing associated data in accordance with the present invention; -
FIG. 6 shows a screen shot depicting associated data in accordance with the present invention; -
FIG. 7 shows a screen shot for managing associated data in accordance with the present invention; and -
FIG. 8 shows a screen shot depicting associated data in accordance with the present invention. -
FIG. 9 shows a system diagram of an implementation of the present invention - The present invention generally relates to systems and methods for performing sensor analytics. More specifically, the present invention relates to systems and methods for associating time/location data points. In an exemplary implementation, a location source having a unique identifier can be associated with a time, a place, or a time and place. One or more demographic profiles can be associated with the time and or place. Multiple time, place and associated demographic profiles can result in the determination of a likely user profile of the unique identifier. The geographic location of the unique identifier with the profile association can then be displayed in real time with other unique identifiers with the same or different profile associations.
- In an implementation, the time and place of the unique identifier, such as the time a mobile telephone is at a specific geographic location, can be associated with one or more demographic profiles, for example, census bureau data. By tracking time and place of the unique identifier along with the associated one or more demographic profiles of each place at the specific time, certain inferences can be made about the unique identifier. By way of example and without limitation, a cellular telephone that is frequently in the warehouse district of city “Metropolis” during normal business hours can be associated with the transportation or logistics business sector. But a cellular telephone that is frequently in the warehouse district of city “Metropolis” during the late night and early morning hours can be associated with the late night entertainment industry.
- Further associations can be made. The cellular telephone that is in the warehouse district during business hours may also be found in suburban retail locations during the early evening hours and in a middle-class suburban neighborhood during the late night and early morning hours. Based on the historical time and location data of the particular cellular telephone and the census data associated with each time and location data point, the user of the first cellular telephone can be assigned a source profile. In the present example the user of the first cellular telephone can generally be associated with groups identifying with middle-class working people leading a largely suburban lifestyle.
- At the same time, further association can also be made about the second cellular telephone that is in the warehouse district during the late night and early morning hours. Continuing with the example, the second cellular telephone may also be found in and around a university campus during business hours and frequently located in a lower rent neighborhood having a high percentage of students during overnight hours. From the demographic data associated with the historical record of the second cellular telephone's time and location data, the user of the second telephone can generally be associated with groups identifying with socially active college or graduate students.
- In both the case of the first cellular telephone and the second cellular telephone meaningful information in the form of a user or source profile was determined by linking or associating various demographic or other information with the times and places that the various location sources, and by extension the user, traveled. The user or source profile was determined without the benefit of a prior registered profile of the user, or without soliciting profiling information such as user or consumer preferences. And the user or source profile was determined without the user choosing which demographic, consumer or user groups he or she would prefer to be associated with. As such, the groups or “tribes” that the user is likely to identify with are an accurate reflection of the user's habits or actual behavior.
- For the purposes herein, a “tribe” is any association of a unique identifier with other unique identifiers that share a common demographic profile or other common association. Tribes can include individuals that are in a particular place at a particular time or individuals that frequent a particular place during a particular occurrence. For example, and without limitation, a tribe can include all individuals that visit a shopping mall on Saturday afternoon or all individuals that visit a shopping mall during a sale or discount event. A tribe can include an association of individuals, devices or other unique identifiers by age, gender, race, religion, national or regional origin, organizational membership or participation, educational level, income level, tax bracket, profession, vocation, occupation, consumer demographical information, political leaning, hobby, interest, activity, geographic location, neighborhood, town, borough, city, county, state, preferred consumer/retail/wholesale provider, event, occurrence, participation in an event or occurrence, time or time period, or any other shared experience in type, time or location between two or more unique identifiers.
- For the purposes herein, a “unique identifier” is any information that identifies a particular person, device, object, event or place at a particular time, occurrence or location. A unique identifier can be a location enable device, such as a cellular telephone, a GPS enabled device, a networked device, a WiFi enabled device, an RFID enabled device, an ATM machine, or any other device that identifies a time/location data point. A unique identifier can also include a place or event that identifies a time/location data point associated with that place or event.
- For the purposes herein, a “time/location data point” is data or other information that identifies a specific event, user, or device at a specific time and/or location. For example, and without limitation, a time/location data point can include: a time stamp associated with a geographic location, such as, the time at a latitude and longitude; a time stamp associated with a specific event at a fixed geographic location, such as, the time of a special or sale at a store or entertainment venue; or the occurrence of an event at a particular time and location, such as, a full taxi cab in the warehouse district at 2:00 am.
- For the purposes herein, an “individualized location data point” is a unique identifier having a time/location data point. An individualized location data point can be associated with one or more tribes.
- In an implementation, one or more individualized data points associated with one or more tribes are displayed on a map. The display is in real time. The display is delayed from real time by a time differential. The display is refreshed according to a predetermined schedule. [predicting the future]
- In an implementation the relative population density of individualized data points comprising a tribe in any given location is displayed. In an implementation, places and events of interest are displayed that are of interest to the tribes displayed. In an implementation, targeted information is displayed with the geographic location and population density of a tribe.
- In an implementation tribe membership of an individualized data point is determined based on historical location and time data. In an implementation tribe membership is determined based on demographic information associated with the time/location data point associated with the individualize data point. In an implementation demographic profiles of one or more individualized data points are derived from tribe membership, time/location data points, demographic information associated with time/location data points, historical data associated and unassociated with a time/location data point, or historical data associated and unassociated with an individualized data point.
- For the purposes herein, “demographic information” and “demographic profile” means any information, historical or derived, which describes or categorizes a particular place, location, event, occurrence, time or period of time, individual, user, device or object, unique identifier, and the like. Demographic information and demographic profile can include, without limitation: Census Bureau data, age, gender, religion, ethnicity, national or regional origin, education level, income level, employment, occupation, vocation, career, hobby, interest, marital status, sexual orientation, consumer preferences, consumer habits, organizational membership and participation, occurrence of an event, geographic location, time or time period, tribe membership and/or tribe association.
- In an exemplary implementation depicted in
FIG. 1 ,mobile device 10 includes a user interface having adisplay 11 on which one or more tribes can be displayed at various geographic locations, such as locations on a city map, at a particular point in time. Inview 12tribes neighborhood 18 andneighborhood 20, at time 12:00:00. Inview 13tribes neighborhood 18 andneighborhood 20 at time 00:00:00. Tribes can be identified on thedisplay 11 bytribe indicators Tribe indicators - In the exemplary implementation of
FIG. 1 , it is apparent thattribe 14 clusters aroundlocation 22 inneighborhood 18 at time 12:00:00.Tribe 14 is also fairly dispersed betweenneighborhoods tribe 16 is fairly dispersed betweenneighborhoods location 24 and 26 inneighborhood 20 at time 00:00:00. - As described further below, knowing demographic information about
neighborhoods locations tribes -
FIG. 2 depicts an exemplary method 200 for associating information with a time/location data point to determine, for example tribe membership, including receiving individualized time/location data points 210; associating the individualized time/location data points withdemographic information 220 and associating the individualized time/location data point with a historical record the unique identifier associated with the individualized time/location data point 230; deriving source profiles, demographic profiles and/or demographic information associated with the individualized time/location data point 240; aggregating two or more individualized time/location data points having associated source ordemographic profiles 250; and displaying the aggregated individualized time/location data points 260. - In
step 210, individualized time/location data is received, for example, at a location based service provider facility. As discussed above, an individualized time/location data point is data or other information that identifies a specific event, user, or device at a specific time and/or location. This can include GPS data from a specific GPS enables device, such as a GPS enabled cellular telephone, navigational device, laptop computer, and the like. This can also include the location of a cellular telephone within the cellular network, i.e., the location of the particular cellular telephone within a particular cell at a particular time. This can also include passive location based services such as ATM machines, which give the time and location of a unique user. This can also include RFID enabled devices such as RFID toll collection services similar to the EZPass system. This can also include the location of a computer within a WiFi network. The examples provided where in are exemplary and not intended to be limiting. The individualized time/location data point is unique to the source of the data, for example, unique to the cellular telephone, ATM debit card, or EZPass RFID transmitter. - Once the location and time of a unique source are received and identified, demographic information can be associated with the time, place or time and place for which the unique source is located. As such, demographic information and profiles are associated 220 with the individualized time/location data point. The demographic information can identify, for example the average income, age, and educational level of residents living in the neighborhood for which the unique identifier is located, as indicated by the individualized time/location data point. The demographic information can include, for example, the consumer trends and profiles associated with individuals who have previously been at the location during the time that the unique identifier also located, as indicated by the individualized time/location data point. As previously discussed, the demographic information that can be associated with the time and/or location can include a variety of information including: Census Bureau data, age, gender, religion, ethnicity, national or regional origin, education level, income level, employment, occupation, vocation, career, hobby, interest, marital status, sexual orientation, consumer preferences, consumer habits, organizational membership and participation, occurrence of an event, geographic location, time or time period, tribe membership and/or tribe association.
- A historical record of the previous locations to which the unique identifier has traveled can also be analyzed and associated 230 with the individualized time/location data point. For example, based on previous locations that the unique identifier has traveled, various tribes may already be attributed to the unique identifier. Additionally, various demographic profiles associated with the previous locations of the unique identifier may also be known. By way of example, a unique identifier that spends four hours every afternoon in an exclusive shopping district can be associated with a number of demographics and/or tribes. But knowing that the same unique identifier spent the previous four hours at a community college in a largely immigrant community adds additional information leading to a smaller set of likely tribal associations.
- After associating 220 demographic information relating to the current individualized time/location data point and associating 230 historical information about the unique identifier of the individualized data point, inferences, profiles, and further informational association can be derived.
Derivation 240 of the associated demographic profiles can include comparing the individualized time/location data point and previous or historical tribal associations with demographic information related to the location and time of the current position of the unique identifier.Derivation 240 allows for further refinement of tribal associations and assignment of new tribal associations. Derived analytics can be obtained. Such analytics include, without limitation, a relative degree of association of the unique identifier with a tribe and or recommendations of places, topics, events or items of interest to a particular tribe. -
Derivation 240 allows for linking and storing 245 of demographic information with the unique identifier for future use inhistorical association 230 as more individualized time/location data points become available. The stored demographic information can be exported to other applications for further analysis. - Once tribal associations of a unique identifier are derived, a plurality of individualized time/location data points having tribal associations are aggregated 250 to determine the location of members of any particular tribe. Analytics can be performed on the aggregated data, including: population density of tribes within a given geographic location, such as the number of middle income individuals over 30 at a shopping mall; the number of tribal members within one or more designated areas at a designated time or time period, such as the number of women under 25 at specific retail locations during a sales event; and the occurrence of an event for a tribal member in a specific location at a specific time, such as the number of a taxi cabs carrying passengers in the late afternoon in the financial district of a city.
- Having aggregated a plurality of individualized time/location data points with associated demographics and derived tribal associations, information about individuals and tribes can be recorded 255 for further processing or displayed 260 to a user. Display 260 of the aggregated derived tribal information can be, for example, to a mobile device, a user terminal such as a personal computer, a networked system display such as an ATM, or a public display.
- In an exemplary implementation as shown in
FIG. 3 , themobile device 310 includesdisplay 311 havingdisplay view 312 showing the location oftribes X including neighborhood tribal icon 314. For example,tribal icon 315 is similar to but smaller thantribal icon 314, thereby indicating fewer tribal members at the location indicated bytribal icon 315. Likewise, tribal icon is similar to but larger thantribal icon 316, thereby indicated more tribal members at the location indicated bytribal icon 317. The relative population density of a tribe can be indicated by any manner of display means including variations in icon size, shape, color, intensity, and the like. Similarly, information relating to tribes, tribe location, tribal population density and the like can be conveyed to the user in graphical or textual format, for example, as icons on a map view or as a list view in a textual document. - In an exemplary implantation as shown in
FIG. 4 , a user interface is provided on amobile device 410 having adisplay 411. View 412 ofdisplay 411 shows a user tribal associations to which the user belongs. As described above, tribal associations are determined by associating the unique identifier of the particular mobile device of the user with a particular place at a particular time to obtain an individualized time/location data point. Demographic and historical information are associated with the individualized data point and the unique identifier to derive certain tribal associations. View 412 displays to the user twotribal associations percentage display user prompt 424 and 425, such as, for example, obtaining information about items of interest to a particular tribe. View 413 depicts additional derived information available to the user, such as for example, recommended items of interest for a particular tribe. The recommended items of interest can include retail locations, services, organizations, places of interest, people of interest, tribes of interest, events and the like. By way of example, view 413 shows that members of Tribe A are also interested in Tribe C. The user can be prompted to obtain more information about the recommended item of interest, as inprompt 430 or to participate in the item of interest, as inprompt 432. -
FIG. 5 depicts another exemplary implementation of a user interface for gaining access to derived information associated with a tribe. For example, the user can be prompted to obtain items of interest to tribe A throughuser prompt 515.FIG. 6 depicts an exemplary implementation ofview 612 showing an item of interest at alocation 640 having a relatively high population density of members of tribe A. Call out 660 can be an interactive window or other user prompt allowing connectivity via the internet, telephone line, email, text message or other media to the item of interest at thelocation 640. -
FIG. 7 depicts an exemplary user interface for managing a user profile associated with a unique identifier and associated demographic and historical information. View 712 ofdisplay 710 shows user prompts 750 for view tribes to which the user may be assigned,user prompt 752 for refreshing or deleting the source profile,account management prompt 754 and other miscellaneous prompts 756. -
FIG. 8 depicts anexemplary user display 711 includingview 712showing advertising information 730 displayed in a window or banner.Advertising information 712 can include any information likely to be of interest to a tribe to which the user belongs or targeted to the user based on tribal affiliation, information in the source profile including associated demographic and historical information, geographic location of the unique identifier, and the like. - Although interactive windows have been shown to indicate user interface options, other means of data selection and input are available including touch screen, keyboard, voice recognition, or physical manipulation of the device. In an exemplary implementation, the location of tribal members can be displayed on the user display of a mobile device at any time by deliberately shaking the device in a repeated manner. An accelerometer embedded within the mobile device sense the shaking of the device and instructs the device to display the current location of the tribal members.
- In other implementations, functionality of the user device, such as a mobile telephone can be linked to derived information available to the user. For example, the alarm function of the mobile telephone can be triggered should the population density of a tribe at a particular location reach a predetermined number. An example can include an alarm trigger if the number of vehicles passing over a bridge or toll booth exceed X number per minute.
-
FIG. 9 depicts a system diagram of an exemplary implementation. System 900 includessystem server 910.System server 910 can include a processor coupled to a computer readable memory. System server is in communication with individualized time/location data pointhistorical file 914 andsource profile 916.Historical file 914 andsource profile 916 can be stored onsystem server 910 or on a secondary storage device (not shown).System server 910 is also in communication withdatabase bank 920.Database bank 920 can include one or more data bases or access to databases includingCensus Database 921,Demographic information database 922,Location database 923,activity database 924, andadvertising database 925. Other databases can be used.System server 910 anddatabase bank 920 are in communication with Derivedassociation engine 930 andaggregation engine 940.System server 910 is also in communication withuser device 950,user terminal 960 and public display 970 vianetwork 980.Network 980 can be the Internet. - In operation,
System server 910 receives an individualized time/location data point from eitheruser device 950 oruser terminal 960. Thesystem server 910 is configured to associate the individualized time/location data point with asource profile 916 and ahistorical file 914. Derivedassociation engine 940 is configured to match demographic information retrieved fromdatabase bank 920 with the individualized time/location data point and associated historical information and assign one or more tribes to the individualized data point. The tribal association is recorded and the historical data file 914 and source file 916 are updated. -
Aggregation engine 940 is configured to compile individualized time/location data points with their associated tribal designations.Aggregation engine 940 is further configured to determine additional derived data relating to the number and frequency of various individualized data points and/or tribal members within a given place, location or time period.Aggregation engine 940 provides the aggregated location of all individualized data points within a tribe along with the additional derived data tosystem server 910.System server 910 then exports the aggregated and derived data touser device 950,user terminal 960 andpublic display 910. The aggregate data can be exported in a data feed for further processing, or displayed on a user display or public display in graphical or tabulated form. - The foregoing description is intended to illustrate various aspects of the present invention. It is not intended that the examples presented herein limit the scope of the present invention. The invention now being fully described, it will be apparent to one of ordinary skill in the art that many changes and modifications can be made thereto without departing from the spirit or scope of the appended claims.
Claims (34)
1. A computer implemented method of conveying aggregate location based information comprising:
receiving one or more individualized datapoints;
associating one or more demographics profiles with the individualized data point;
aggregating the individualized datapoint and associated demographic with a second location data point having a second associated demographic profile; and
exporting the aggregate location data.
2. The computer implemented method of claim 1 wherein the received individualized data is associated with an individual user.
3. The computer implemented method of claim 1 wherein the received individualized data point is associated with an individual location enabled device.
4. The computer implemented method of claim 1 wherein the received individualized data point is associated with a mobile device.
5. The computer implemented method of claim 1 wherein the received individualized data point is anonymously associated with a specific user.
6. The computer implemented method of claim 5 wherein in the received individualized data point is associated with at least one user and received from a data provider or data aggregator.
7. The computer implemented method of claim 1 wherein individualized data is received in real time.
8. The computer implemented method of claim 1 wherein the individualized data is received according to a predetermined schedule.
9. The computer implemented method of claim 1 wherein individualized data is received according to a source profile.
10. The computer implemented method of claim 1 wherein the received one or more individualized datapoints is associated with a historical file.
11. The computer implemented method of claim 9 wherein the association of the source profile with the individualized datapoint maintains the anonymity of the user.
12. The computer implemented method of claim 1 wherein the demographic profile comprises historical location data points.
13. The computer implemented method of claim 1 wherein the demographic profile comprises information from the group comprising: Census Bureau data, financial demographics, social demographics, tribe/group demographics, historical demographical information; derived demographic information; gender; race; educational level; historical geographic information; or user entered information/preferences.
14. The computer implemented method of claim 1 wherein associating further comprises disassociating the individualized data point from any historical associated demographics.
15. The computer implemented method of claim 1 wherein associating further comprises selectively disassociating historical associated demographics from the individualized data point.
16. The computer implemented method of claim 1 wherein associating further comprises disassociating the individualized data point from any historical location information.
17. The computer implemented method of claim 1 wherein associating further comprises selectively disassociating historical location information from the individualized data point.
18. The computer implemented method of claim 1 wherein the individualized datapoint and associated demographic and the second individualized data point and second associated demographic are related to the same user.
19. The computer implemented method of claim 1 wherein the individualized datapoint and associated demographic and the second individualized data point and second associated demographic are unrelated to the same user.
20. The computer implemented method of claim 1 wherein aggregating further comprises deriving one or more tribes related to the individualized datapoint, associated demographic, second individualized data point, and second associated demographic.
21. The computer implemented method of claim 1 wherein aggregating further comprises identifying the individualized data point with one or more tribes based on a derived associated demographic
22. The computer implemented method of claim 1 wherein aggregating further comprises recommending items of interest associated with a tribe.
23. The computer implemented method of claim 1 wherein aggregating further comprises recommending items of interest associated with a historical record of an individualized data point.
24. The computer implemented method of claim 1 wherein aggregating further comprises identifying the individualized datapoint with all possible tribes of interest.
25. The computer implemented method of claim 1 wherein aggregating further comprises indexing tribe activity based on tribe historical location data with one or more indicators.
26. The computer implemented method of claim 1 wherein aggregating further comprises linking consumer information with the individualized datapoint based on tribes of interest to the individualized data point.
27. The computer implemented method of claim 1 wherein a plurality of individualized data points associated and aggregated with a tribe are exported to a display on a user interface.
28. The computer implemented method of claim 1 wherein a plurality of individualized data points are exported to a display including a map of an area of interest.
29. The computer implemented method of claim 1 wherein a plurality of individualized data points are exported to a display in real time.
30. The computer implemented method of claim 1 wherein all tribes associated with an individualized data point are exported to a display including an area of interest.
31. The computer implemented method of claim 1 wherein tribes are selectively displayed on a map of an area of interest.
32. The computer implemented method of claim 1 wherein items of interest associated with a tribe are displayed on a map of an area of interest.
33. A computer readable medium having stored thereon a computer program that, when executed, causes a computer to perform the steps of:
receiving one or more individualized data points;
associating one or more demographics profiles with the individualized data point;
aggregating the individualized data point and associated demographic with a second location data point having a second associated demographic profile; and
exporting the aggregated individualized data point and second location data point.
34. A system for determining and conveying aggregate location based information comprising:
a network;
one or more location enabled user devices in communication with the network, wherein the one or more location enabled user devices have an individualized location data point; and
a processor in communication with the network, wherein the processor receives one or more individualized location data points from the one or more location enabled user devices, the processor associates the one or more individualized location data points with one or more demographic profiles and aggregates the individualized location data point having the associated demographic profile with a second location data point having a second associated demographic profile, and exports the aggregated individualized location data point and the second location data point to the network.
Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US12/134,634 US20090307263A1 (en) | 2008-06-06 | 2008-06-06 | System And Method Of Performing Location Analytics |
US13/304,111 US8959098B2 (en) | 2008-06-06 | 2011-11-23 | System and method of performing location analytics |
US14/595,942 US9571962B2 (en) | 2008-06-06 | 2015-01-13 | System and method of performing location analytics |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US12/134,634 US20090307263A1 (en) | 2008-06-06 | 2008-06-06 | System And Method Of Performing Location Analytics |
Related Child Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US13/304,111 Continuation US8959098B2 (en) | 2008-06-06 | 2011-11-23 | System and method of performing location analytics |
Publications (1)
Publication Number | Publication Date |
---|---|
US20090307263A1 true US20090307263A1 (en) | 2009-12-10 |
Family
ID=41401252
Family Applications (3)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US12/134,634 Abandoned US20090307263A1 (en) | 2008-06-06 | 2008-06-06 | System And Method Of Performing Location Analytics |
US13/304,111 Active US8959098B2 (en) | 2008-06-06 | 2011-11-23 | System and method of performing location analytics |
US14/595,942 Active US9571962B2 (en) | 2008-06-06 | 2015-01-13 | System and method of performing location analytics |
Family Applications After (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US13/304,111 Active US8959098B2 (en) | 2008-06-06 | 2011-11-23 | System and method of performing location analytics |
US14/595,942 Active US9571962B2 (en) | 2008-06-06 | 2015-01-13 | System and method of performing location analytics |
Country Status (1)
Country | Link |
---|---|
US (3) | US20090307263A1 (en) |
Cited By (23)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100117793A1 (en) * | 2007-03-29 | 2010-05-13 | Fujitsu Limited | Photographing control apparatus, program and method of the same, and photographing apparatus |
US20100151816A1 (en) * | 2008-12-16 | 2010-06-17 | Jan Besehanic | Methods and apparatus for associating media devices with a demographic composition of a geographic area |
US20100198917A1 (en) * | 2009-02-02 | 2010-08-05 | Kota Enterprises, Llc | Crowd formation for mobile device users |
US20100273139A1 (en) * | 2009-04-27 | 2010-10-28 | Citysearch, LLC | Method and system for providing an answer |
US20110207440A1 (en) * | 2010-02-25 | 2011-08-25 | Qualcomm Incorporated | Mobile device profile aggregation |
US20120047152A1 (en) * | 2009-04-29 | 2012-02-23 | Waldeck Technology, Llc | System and method for profile tailoring in an aggregate profiling system |
US8340685B2 (en) | 2010-08-25 | 2012-12-25 | The Nielsen Company (Us), Llc | Methods, systems and apparatus to generate market segmentation data with anonymous location data |
US20130054358A1 (en) * | 2011-08-24 | 2013-02-28 | Bank Of America | Computer System for Identifying Green Merchants Within a Range of a Mobile Device |
US20130073553A1 (en) * | 2011-09-15 | 2013-03-21 | Fujitsu Limited | Information management method and information management apparatus |
US20130073550A1 (en) * | 2011-09-15 | 2013-03-21 | Fujitsu Limited | Information management method and information management apparatus |
US20130110683A1 (en) * | 2011-11-01 | 2013-05-02 | Sap Ag | Hybrid Context-Sensitive Matching Algorithm for Retrieving Product Catalogue Information |
US8473512B2 (en) | 2009-11-06 | 2013-06-25 | Waldeck Technology, Llc | Dynamic profile slice |
US8489445B1 (en) * | 2008-12-19 | 2013-07-16 | Amazon Technologies, Inc. | Determining and displaying item preferences associated with geographic areas |
US8620532B2 (en) | 2009-03-25 | 2013-12-31 | Waldeck Technology, Llc | Passive crowd-sourced map updates and alternate route recommendations |
US8782560B2 (en) | 2009-12-22 | 2014-07-15 | Waldeck Technology, Llc | Relative item of interest explorer interface |
US8898288B2 (en) | 2010-03-03 | 2014-11-25 | Waldeck Technology, Llc | Status update propagation based on crowd or POI similarity |
US20150006255A1 (en) * | 2013-06-28 | 2015-01-01 | Streetlight Data, Inc. | Determining demographic data |
JP2015095195A (en) * | 2013-11-13 | 2015-05-18 | Kddi株式会社 | Terminal management device and method |
US9449279B2 (en) | 2010-06-24 | 2016-09-20 | The Nielsen Company (Us), Llc | Network server arrangements for processing non-parametric, multi-dimensional, spatial and temporal human behavior or technical observations measured pervasively, and related methods for the same |
US9763048B2 (en) | 2009-07-21 | 2017-09-12 | Waldeck Technology, Llc | Secondary indications of user locations and use thereof by a location-based service |
US9886727B2 (en) | 2010-11-11 | 2018-02-06 | Ikorongo Technology, LLC | Automatic check-ins and status updates |
US10454863B2 (en) * | 2014-05-02 | 2019-10-22 | Samsung Electronics Co., Ltd. | Data processing device and data processing method based on user emotion icon activity |
US11502914B2 (en) | 2009-05-08 | 2022-11-15 | The Nielsen Company (Us), Llc | Systems and methods for behavioural and contextual data analytics |
Families Citing this family (25)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8369264B2 (en) | 2005-10-28 | 2013-02-05 | Skyhook Wireless, Inc. | Method and system for selecting and providing a relevant subset of Wi-Fi location information to a mobile client device so the client device may estimate its position with efficient utilization of resources |
EP2503832B1 (en) | 2005-02-22 | 2019-08-21 | Skyhook Wireless, Inc. | Method for calculating the position of WiFi-enabled devices |
US20090307263A1 (en) * | 2008-06-06 | 2009-12-10 | Sense Networks, Inc. | System And Method Of Performing Location Analytics |
US9253605B2 (en) * | 2010-03-24 | 2016-02-02 | Skyhook Wireless, Inc. | System and method for resolving multiple location estimate conflicts in a WLAN-positioning system |
WO2011156549A2 (en) | 2010-06-11 | 2011-12-15 | Skyhook Wireless, Inc. | Methods of and systems for measuring beacon stability of wireless access points |
WO2012121950A1 (en) * | 2011-03-04 | 2012-09-13 | Walker Tristan | System and method for managing and redeeming offers with a location-based service |
US20120331561A1 (en) * | 2011-06-22 | 2012-12-27 | Broadstone Andrew J | Method of and Systems for Privacy Preserving Mobile Demographic Measurement of Individuals, Groups and Locations Over Time and Space |
KR20130096978A (en) * | 2012-02-23 | 2013-09-02 | 삼성전자주식회사 | User terminal device, server, information providing system based on situation and method thereof |
US20140012806A1 (en) * | 2012-06-22 | 2014-01-09 | Jiwire, Inc. | Location graph based derivation of attributes |
US9418075B2 (en) * | 2012-07-18 | 2016-08-16 | Google Inc. | Automatic meta-neighborhood and annotation generation for maps |
US20140149491A1 (en) * | 2012-11-28 | 2014-05-29 | Christian Rivadalla | Real-Time Affinity- and Proximity-Based Monitoring and Control System and Method and Correlation Engine Therefor |
US10304325B2 (en) | 2013-03-13 | 2019-05-28 | Arris Enterprises Llc | Context health determination system |
US9135248B2 (en) | 2013-03-13 | 2015-09-15 | Arris Technology, Inc. | Context demographic determination system |
US9692839B2 (en) | 2013-03-13 | 2017-06-27 | Arris Enterprises, Inc. | Context emotion determination system |
US20150005007A1 (en) * | 2013-06-28 | 2015-01-01 | Streetlight Data, Inc. | Displaying demographic data |
US9307360B1 (en) | 2015-01-09 | 2016-04-05 | NinthDecimal, Inc. | Systems and methods to identify a predefined geographical region in which a mobile device is located |
US10327094B2 (en) | 2016-06-07 | 2019-06-18 | NinthDecimal, Inc. | Systems and methods to track locations visited by mobile devices and determine neighbors of and distances among locations |
US9291700B1 (en) | 2015-01-09 | 2016-03-22 | NinthDecimal, Inc. | Systems and methods to identify home addresses of mobile devices |
US9860704B2 (en) * | 2015-03-31 | 2018-01-02 | Foursquare Labs, Inc. | Venue identification from wireless scan data |
US9615236B2 (en) * | 2015-05-28 | 2017-04-04 | International Business Machines Corporation | Freeing up mobile network for important phone calls in case of disaster |
CN106557942B (en) * | 2015-09-30 | 2020-07-10 | 百度在线网络技术(北京)有限公司 | User relationship identification method and device |
US10530896B2 (en) | 2016-02-24 | 2020-01-07 | International Business Machines Corporation | Contextual remote management of virtual app lifecycle |
US9667772B1 (en) * | 2016-06-17 | 2017-05-30 | International Business Machines Corporation | Transient, context-dependent grouping of content for mobile device display |
US20190333085A1 (en) | 2018-04-25 | 2019-10-31 | International Business Machines Corporation | Identifying geographic market share |
US10783205B2 (en) | 2018-07-25 | 2020-09-22 | International Business Machines Corporation | Mobile device having cognitive contacts |
Citations (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6038559A (en) * | 1998-03-16 | 2000-03-14 | Navigation Technologies Corporation | Segment aggregation in a geographic database and methods for use thereof in a navigation application |
US20010029506A1 (en) * | 2000-02-17 | 2001-10-11 | Alison Lee | System, method, and program product for navigating and mapping content at a Web site |
US20010049636A1 (en) * | 2000-04-17 | 2001-12-06 | Amir Hudda | System and method for wireless purchases of goods and services |
US6408278B1 (en) * | 1998-11-10 | 2002-06-18 | I-Open.Com, Llc | System and method for delivering out-of-home programming |
US20020111852A1 (en) * | 2001-01-16 | 2002-08-15 | Levine Robyn R. | Business offering content delivery |
US20040036224A1 (en) * | 2000-09-26 | 2004-02-26 | Crompton Gordon James | Amusement machine |
US6704787B1 (en) * | 1999-12-03 | 2004-03-09 | Intercard Payments, Inc. | Date of birth authentication system and method using demographic and/or geographic data supplied by a subscriber that is verified by a third party |
US20040117358A1 (en) * | 2002-03-16 | 2004-06-17 | Von Kaenel Tim A. | Method, system, and program for an improved enterprise spatial system |
US20050143909A1 (en) * | 2003-12-31 | 2005-06-30 | Orwant Jonathan L. | Technique for collecting and using information about the geographic position of a mobile object on the earth's surface |
US20060074883A1 (en) * | 2004-10-05 | 2006-04-06 | Microsoft Corporation | Systems, methods, and interfaces for providing personalized search and information access |
US20060085177A1 (en) * | 2004-10-19 | 2006-04-20 | Microsoft Corporation | Modeling location histories |
US20060223505A1 (en) * | 2005-03-31 | 2006-10-05 | Starr Robert J | Methods, systems, and products for demographic discounting |
US7292963B2 (en) * | 2004-10-29 | 2007-11-06 | Sap Aktiengesellschaft | Aggregating sensor data |
US20080005674A1 (en) * | 2006-06-30 | 2008-01-03 | Wattenberg Martin M | System and method for visually analyzing geographic data |
US20080082472A1 (en) * | 2005-04-04 | 2008-04-03 | Spadac Inc. | Event, threat and result change detection system and method |
US20080188261A1 (en) * | 2007-02-02 | 2008-08-07 | Miles Arnone | Mediated social network |
Family Cites Families (46)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6604083B1 (en) * | 1997-06-12 | 2003-08-05 | G. William Bailey | Market determination based on travel time bands |
US20010011226A1 (en) * | 1997-06-25 | 2001-08-02 | Paul Greer | User demographic profile driven advertising targeting |
AU751177B2 (en) * | 1997-07-16 | 2002-08-08 | Paul Michael O'connor | Method and system for compiling demographic data |
US6129274A (en) * | 1998-06-09 | 2000-10-10 | Fujitsu Limited | System and method for updating shopping transaction history using electronic personal digital shopping assistant |
US7720723B2 (en) * | 1998-09-18 | 2010-05-18 | Amazon Technologies, Inc. | User interface and methods for recommending items to users |
US6522875B1 (en) * | 1998-11-17 | 2003-02-18 | Eric Morgan Dowling | Geographical web browser, methods, apparatus and systems |
US6968333B2 (en) * | 2000-04-02 | 2005-11-22 | Tangis Corporation | Soliciting information based on a computer user's context |
US6963850B1 (en) * | 1999-04-09 | 2005-11-08 | Amazon.Com, Inc. | Computer services for assisting users in locating and evaluating items in an electronic catalog based on actions performed by members of specific user communities |
US6353398B1 (en) * | 1999-10-22 | 2002-03-05 | Himanshu S. Amin | System for dynamically pushing information to a user utilizing global positioning system |
CA2298194A1 (en) | 2000-02-07 | 2001-08-07 | Profilium Inc. | Method and system for delivering and targeting advertisements over wireless networks |
GB0002985D0 (en) * | 2000-02-09 | 2000-03-29 | Travelfusion Limited | Integrated journey planner |
AU2002213226A1 (en) * | 2000-10-16 | 2002-04-29 | Engage Technologies | Demographic profiling engine |
US7065550B2 (en) * | 2001-02-14 | 2006-06-20 | International Business Machines Corporation | Information provision over a network based on a user's profile |
US20020174428A1 (en) * | 2001-03-28 | 2002-11-21 | Philips Electronics North America Corp. | Method and apparatus for generating recommendations for a plurality of users |
US20030040850A1 (en) * | 2001-08-07 | 2003-02-27 | Amir Najmi | Intelligent adaptive optimization of display navigation and data sharing |
US20030064350A1 (en) * | 2001-10-01 | 2003-04-03 | Gilles Rubinstenn | Beauty advisory system and method |
US7162522B2 (en) * | 2001-11-02 | 2007-01-09 | Xerox Corporation | User profile classification by web usage analysis |
US20030135494A1 (en) * | 2002-01-15 | 2003-07-17 | Jeffrey Phelan | Method and apparatus for distributing information based on a geographic location profile of a user |
WO2003081391A2 (en) * | 2002-03-19 | 2003-10-02 | Mapinfo Corporation | Location based service provider |
US20040044549A1 (en) * | 2002-08-30 | 2004-03-04 | Loop Kevin S. | Method of determining potential for repair services in a geographic area |
US20070262860A1 (en) * | 2006-04-23 | 2007-11-15 | Robert Salinas | Distribution of Targeted Messages and the Serving, Collecting, Managing, and Analyzing and Reporting of Information relating to Mobile and other Electronic Devices |
US20040162830A1 (en) * | 2003-02-18 | 2004-08-19 | Sanika Shirwadkar | Method and system for searching location based information on a mobile device |
US7464155B2 (en) * | 2003-03-24 | 2008-12-09 | Siemens Canada Ltd. | Demographic information acquisition system |
US7310676B2 (en) * | 2004-02-09 | 2007-12-18 | Proxpro, Inc. | Method and computer system for matching mobile device users for business and social networking |
US7849031B2 (en) * | 2004-12-22 | 2010-12-07 | Hntb Holdings Ltd. | Optimizing traffic predictions and enhancing notifications |
US20060195361A1 (en) * | 2005-10-01 | 2006-08-31 | Outland Research | Location-based demographic profiling system and method of use |
JP5265077B2 (en) * | 2005-01-18 | 2013-08-14 | パイオニア株式会社 | Map distribution device, map acquisition device, map processing system, map distribution method, map acquisition method, map distribution program, map acquisition program, and recording medium |
JP4698281B2 (en) * | 2005-05-09 | 2011-06-08 | ソニー・エリクソン・モバイルコミュニケーションズ株式会社 | Mobile terminal, information recommendation method and program |
US7848765B2 (en) * | 2005-05-27 | 2010-12-07 | Where, Inc. | Location-based services |
US20060266830A1 (en) * | 2005-05-31 | 2006-11-30 | Horozov Tzvetan T | Location-based recommendation system |
US20070005419A1 (en) * | 2005-06-30 | 2007-01-04 | Microsoft Corporation | Recommending location and services via geospatial collaborative filtering |
EP1935204A4 (en) * | 2005-09-23 | 2013-04-03 | Grape Technology Group Inc | Enhanced directory assistance system and method including location and search functions |
US20070156435A1 (en) * | 2006-01-05 | 2007-07-05 | Greening Daniel R | Personalized geographic directory |
US8989778B2 (en) * | 2006-06-01 | 2015-03-24 | Green Dot Corporation | Secure and private location sharing for location-aware mobile communication devices |
US20070281690A1 (en) * | 2006-06-01 | 2007-12-06 | Flipt, Inc | Displaying and tagging places of interest on location-aware mobile communication devices in a local area network |
US20080104225A1 (en) * | 2006-11-01 | 2008-05-01 | Microsoft Corporation | Visualization application for mining of social networks |
US8108414B2 (en) * | 2006-11-29 | 2012-01-31 | David Stackpole | Dynamic location-based social networking |
US7937380B2 (en) * | 2006-12-22 | 2011-05-03 | Yahoo! Inc. | System and method for recommended events |
US9392074B2 (en) * | 2007-07-07 | 2016-07-12 | Qualcomm Incorporated | User profile generation architecture for mobile content-message targeting |
US8775960B1 (en) * | 2008-03-10 | 2014-07-08 | United Services Automobile Association (Usaa) | Systems and methods for geographic mapping and review |
US20090307263A1 (en) * | 2008-06-06 | 2009-12-10 | Sense Networks, Inc. | System And Method Of Performing Location Analytics |
US8224766B2 (en) * | 2008-09-30 | 2012-07-17 | Sense Networks, Inc. | Comparing spatial-temporal trails in location analytics |
US8386519B2 (en) * | 2008-12-30 | 2013-02-26 | Expanse Networks, Inc. | Pangenetic web item recommendation system |
US10042032B2 (en) * | 2009-04-29 | 2018-08-07 | Amazon Technologies, Inc. | System and method for generating recommendations based on similarities between location information of multiple users |
US8825759B1 (en) * | 2010-02-08 | 2014-09-02 | Google Inc. | Recommending posts to non-subscribing users |
EP2518680A1 (en) * | 2011-04-28 | 2012-10-31 | RapidBlue Solutions Oy | Location based consumer profiling |
-
2008
- 2008-06-06 US US12/134,634 patent/US20090307263A1/en not_active Abandoned
-
2011
- 2011-11-23 US US13/304,111 patent/US8959098B2/en active Active
-
2015
- 2015-01-13 US US14/595,942 patent/US9571962B2/en active Active
Patent Citations (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6038559A (en) * | 1998-03-16 | 2000-03-14 | Navigation Technologies Corporation | Segment aggregation in a geographic database and methods for use thereof in a navigation application |
US6408278B1 (en) * | 1998-11-10 | 2002-06-18 | I-Open.Com, Llc | System and method for delivering out-of-home programming |
US6704787B1 (en) * | 1999-12-03 | 2004-03-09 | Intercard Payments, Inc. | Date of birth authentication system and method using demographic and/or geographic data supplied by a subscriber that is verified by a third party |
US20010029506A1 (en) * | 2000-02-17 | 2001-10-11 | Alison Lee | System, method, and program product for navigating and mapping content at a Web site |
US20010049636A1 (en) * | 2000-04-17 | 2001-12-06 | Amir Hudda | System and method for wireless purchases of goods and services |
US20040036224A1 (en) * | 2000-09-26 | 2004-02-26 | Crompton Gordon James | Amusement machine |
US20020111852A1 (en) * | 2001-01-16 | 2002-08-15 | Levine Robyn R. | Business offering content delivery |
US20040117358A1 (en) * | 2002-03-16 | 2004-06-17 | Von Kaenel Tim A. | Method, system, and program for an improved enterprise spatial system |
US20050143909A1 (en) * | 2003-12-31 | 2005-06-30 | Orwant Jonathan L. | Technique for collecting and using information about the geographic position of a mobile object on the earth's surface |
US20060074883A1 (en) * | 2004-10-05 | 2006-04-06 | Microsoft Corporation | Systems, methods, and interfaces for providing personalized search and information access |
US20060085177A1 (en) * | 2004-10-19 | 2006-04-20 | Microsoft Corporation | Modeling location histories |
US7292963B2 (en) * | 2004-10-29 | 2007-11-06 | Sap Aktiengesellschaft | Aggregating sensor data |
US20060223505A1 (en) * | 2005-03-31 | 2006-10-05 | Starr Robert J | Methods, systems, and products for demographic discounting |
US20080082472A1 (en) * | 2005-04-04 | 2008-04-03 | Spadac Inc. | Event, threat and result change detection system and method |
US20080005674A1 (en) * | 2006-06-30 | 2008-01-03 | Wattenberg Martin M | System and method for visually analyzing geographic data |
US20080188261A1 (en) * | 2007-02-02 | 2008-08-07 | Miles Arnone | Mediated social network |
Cited By (57)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100117793A1 (en) * | 2007-03-29 | 2010-05-13 | Fujitsu Limited | Photographing control apparatus, program and method of the same, and photographing apparatus |
US11783356B2 (en) | 2008-12-16 | 2023-10-10 | The Nielsen Company (Us), Llc | Methods and apparatus for associating media devices with a demographic composition of a geographic area |
US20100151816A1 (en) * | 2008-12-16 | 2010-06-17 | Jan Besehanic | Methods and apparatus for associating media devices with a demographic composition of a geographic area |
US8812012B2 (en) | 2008-12-16 | 2014-08-19 | The Nielsen Company (Us), Llc | Methods and apparatus for associating media devices with a demographic composition of a geographic area |
US10078846B2 (en) | 2008-12-16 | 2018-09-18 | The Nielsen Company (Us), Llc | Methods and apparatus for associating media devices with a demographic composition of a geographic area |
US10685365B2 (en) | 2008-12-16 | 2020-06-16 | The Nielsen Company (Us), Llc | Methods and apparatus for associating media devices with a demographic composition of a geographic area |
US10956923B2 (en) | 2008-12-16 | 2021-03-23 | The Nielsen Company (Us), Llc | Methods and apparatus for associating media devices with a demographic composition of a geographic area |
US11556946B2 (en) | 2008-12-16 | 2023-01-17 | The Nielsen Company (Us), Llc | Methods and apparatus for associating media devices with a demographic composition of a geographic area |
US9916593B1 (en) * | 2008-12-19 | 2018-03-13 | Amazon Technologies, Inc. | Determining and displaying item preferences associated with geographic areas |
US8489445B1 (en) * | 2008-12-19 | 2013-07-16 | Amazon Technologies, Inc. | Determining and displaying item preferences associated with geographic areas |
US9098723B2 (en) | 2009-02-02 | 2015-08-04 | Waldeck Technology, Llc | Forming crowds and providing access to crowd data in a mobile environment |
US9641393B2 (en) | 2009-02-02 | 2017-05-02 | Waldeck Technology, Llc | Forming crowds and providing access to crowd data in a mobile environment |
US8918398B2 (en) * | 2009-02-02 | 2014-12-23 | Waldeck Technology, Llc | Maintaining a historical record of anonymized user profile data by location for users in a mobile environment |
US20100198917A1 (en) * | 2009-02-02 | 2010-08-05 | Kota Enterprises, Llc | Crowd formation for mobile device users |
US20100198826A1 (en) * | 2009-02-02 | 2010-08-05 | Kota Enterprises, Llc | Maintaining a historical record of anonymized user profile data by location for users in a mobile environment |
US9397890B2 (en) * | 2009-02-02 | 2016-07-19 | Waldeck Technology Llc | Serving a request for data from a historical record of anonymized user profile data in a mobile environment |
US8495065B2 (en) * | 2009-02-02 | 2013-07-23 | Waldeck Technology, Llc | Maintaining a historical record of anonymized user profile data by location for users in a mobile environment |
US20100198870A1 (en) * | 2009-02-02 | 2010-08-05 | Kota Enterprises, Llc | Serving a request for data from a historical record of anonymized user profile data in a mobile environment |
US20130282723A1 (en) * | 2009-02-02 | 2013-10-24 | Waldeck Technology, Llc | Maintaining A Historical Record Of Anonymized User Profile Data By Location For Users In A Mobile Environment |
US20100198828A1 (en) * | 2009-02-02 | 2010-08-05 | Kota Enterprises, Llc | Forming crowds and providing access to crowd data in a mobile environment |
US8620532B2 (en) | 2009-03-25 | 2013-12-31 | Waldeck Technology, Llc | Passive crowd-sourced map updates and alternate route recommendations |
US8868550B2 (en) * | 2009-04-27 | 2014-10-21 | Citysearch, LLC | Method and system for providing an answer |
US20100273139A1 (en) * | 2009-04-27 | 2010-10-28 | Citysearch, LLC | Method and system for providing an answer |
US8554770B2 (en) * | 2009-04-29 | 2013-10-08 | Waldeck Technology, Llc | Profile construction using location-based aggregate profile information |
US20120047184A1 (en) * | 2009-04-29 | 2012-02-23 | Waldeck Technology, Llc | Profile construction using location-based aggregate profile information |
US9053169B2 (en) | 2009-04-29 | 2015-06-09 | Waldeck Technology, Llc | Profile construction using location-based aggregate profile information |
US20120047152A1 (en) * | 2009-04-29 | 2012-02-23 | Waldeck Technology, Llc | System and method for profile tailoring in an aggregate profiling system |
US11502914B2 (en) | 2009-05-08 | 2022-11-15 | The Nielsen Company (Us), Llc | Systems and methods for behavioural and contextual data analytics |
US9763048B2 (en) | 2009-07-21 | 2017-09-12 | Waldeck Technology, Llc | Secondary indications of user locations and use thereof by a location-based service |
US8473512B2 (en) | 2009-11-06 | 2013-06-25 | Waldeck Technology, Llc | Dynamic profile slice |
US9300704B2 (en) | 2009-11-06 | 2016-03-29 | Waldeck Technology, Llc | Crowd formation based on physical boundaries and other rules |
US8782560B2 (en) | 2009-12-22 | 2014-07-15 | Waldeck Technology, Llc | Relative item of interest explorer interface |
US9020534B2 (en) | 2010-02-25 | 2015-04-28 | Qualcomm Incorporated | Location-based mobile device profile aggregation |
WO2011106653A1 (en) * | 2010-02-25 | 2011-09-01 | Qualcomm Incorporated | Mobile device profile aggregation |
US20110207440A1 (en) * | 2010-02-25 | 2011-08-25 | Qualcomm Incorporated | Mobile device profile aggregation |
US8898288B2 (en) | 2010-03-03 | 2014-11-25 | Waldeck Technology, Llc | Status update propagation based on crowd or POI similarity |
US9449279B2 (en) | 2010-06-24 | 2016-09-20 | The Nielsen Company (Us), Llc | Network server arrangements for processing non-parametric, multi-dimensional, spatial and temporal human behavior or technical observations measured pervasively, and related methods for the same |
US11170410B2 (en) | 2010-08-25 | 2021-11-09 | The Nielsen Company (Us), Llc | Methods, systems and apparatus to generate market segmentation data with anonymous location data |
US9996855B2 (en) | 2010-08-25 | 2018-06-12 | The Nielsen Company (Us), Llc | Methods, systems and apparatus to generate market segmentation data with anonymous location data |
US9613363B2 (en) | 2010-08-25 | 2017-04-04 | The Nielsen Company (Us), Llc | Methods, systems and apparatus to generate market segmentation data with anonymous location data |
US8954090B2 (en) | 2010-08-25 | 2015-02-10 | The Nielson Company (Us), Llc | Methods, systems and apparatus to generate market segmentation data with anonymous location data |
US11769174B2 (en) | 2010-08-25 | 2023-09-26 | The Nielsen Company (Us), Llc | Methods, systems and apparatus to generate market segmentation data with anonymous location data |
US10380643B2 (en) | 2010-08-25 | 2019-08-13 | The Nielsen Company (Us), Llc | Methods, systems and apparatus to generate market segmentation data with anonymous location data |
US8340685B2 (en) | 2010-08-25 | 2012-12-25 | The Nielsen Company (Us), Llc | Methods, systems and apparatus to generate market segmentation data with anonymous location data |
US10713687B2 (en) | 2010-08-25 | 2020-07-14 | The Nielsen Company (Us), Llc | Methods, systems and apparatus to generate market segmentation data with anonymous location data |
US9886727B2 (en) | 2010-11-11 | 2018-02-06 | Ikorongo Technology, LLC | Automatic check-ins and status updates |
US11449904B1 (en) | 2010-11-11 | 2022-09-20 | Ikorongo Technology, LLC | System and device for generating a check-in image for a geographic location |
US20130054358A1 (en) * | 2011-08-24 | 2013-02-28 | Bank Of America | Computer System for Identifying Green Merchants Within a Range of a Mobile Device |
US20130073550A1 (en) * | 2011-09-15 | 2013-03-21 | Fujitsu Limited | Information management method and information management apparatus |
US9223801B2 (en) * | 2011-09-15 | 2015-12-29 | Fujitsu Limited | Information management method and information management apparatus |
US20130073553A1 (en) * | 2011-09-15 | 2013-03-21 | Fujitsu Limited | Information management method and information management apparatus |
US8849792B2 (en) * | 2011-09-15 | 2014-09-30 | Fujitsu Limited | Information management method and information management apparatus |
US20130110683A1 (en) * | 2011-11-01 | 2013-05-02 | Sap Ag | Hybrid Context-Sensitive Matching Algorithm for Retrieving Product Catalogue Information |
US8756120B2 (en) * | 2011-11-01 | 2014-06-17 | Sap Ag | Hybrid context-sensitive matching algorithm for retrieving product catalogue information |
US20150006255A1 (en) * | 2013-06-28 | 2015-01-01 | Streetlight Data, Inc. | Determining demographic data |
JP2015095195A (en) * | 2013-11-13 | 2015-05-18 | Kddi株式会社 | Terminal management device and method |
US10454863B2 (en) * | 2014-05-02 | 2019-10-22 | Samsung Electronics Co., Ltd. | Data processing device and data processing method based on user emotion icon activity |
Also Published As
Publication number | Publication date |
---|---|
US20120071175A1 (en) | 2012-03-22 |
US8959098B2 (en) | 2015-02-17 |
US9571962B2 (en) | 2017-02-14 |
US20150304807A1 (en) | 2015-10-22 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US9571962B2 (en) | System and method of performing location analytics | |
US8224766B2 (en) | Comparing spatial-temporal trails in location analytics | |
US10445777B2 (en) | Methods and systems for delivering electronic content to users in population based geographic zones | |
US9574899B2 (en) | Systems and method for determination and display of personalized distance | |
US20190158609A1 (en) | System and method for improved mapping and routing | |
US20190130426A1 (en) | Measuring retail visitation amounts based on locations sensed by mobile devices | |
US11887164B2 (en) | Personalized information from venues of interest | |
US10423983B2 (en) | Determining targeting information based on a predictive targeting model | |
US10467656B2 (en) | Online to offline commerce merchant advertising | |
US20170200174A1 (en) | Computerized systems and methods of mapping attention based on w4 data related to a user | |
US20140108540A1 (en) | Method of conducting social network application operations | |
US20120109752A1 (en) | Systems and methods for delivering targeted content to a consumer's mobile device based on the consumer's physical location and social media memberships | |
US20100082301A1 (en) | Event Identification In Sensor Analytics | |
US10002194B2 (en) | Event location with social network integration | |
US20100082403A1 (en) | Advocate rank network & engine | |
US20160225026A1 (en) | Systems and methods for presenting and delivering content | |
JP2012510113A (en) | Provision of digital contents based on expected user behavior | |
US9773067B2 (en) | Personal intelligence platform | |
US20160050535A1 (en) | Determining recipient location | |
US9002883B1 (en) | Providing aggregated starting point information | |
US20140129334A1 (en) | Method and system for modeling consumer activity areas based on social media and mobile data | |
US9967352B2 (en) | Communication system with location based services mechanism and method of operation thereof | |
CN112241489B (en) | Information pushing method, device, readable storage medium and computer equipment | |
US10545028B1 (en) | System and method of generating route-based ad networks | |
Križo et al. | Using the concept of solomo marketing in digital environment to increase brand awareness and communication with customers |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: SENSE NETWORKS, INC., NEW YORK Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:SKIBISKI, GREG;PENTLAND, ALEX (SANDY);JEBARA, TONY;AND OTHERS;REEL/FRAME:021797/0955 Effective date: 20080606 |
|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |