# US 2014/0195530 A1 · Apparatus and method for profiling users > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2014/0195530 A1 - Document ID: US20140195530A1 - Status: Published application - Kind: A1 - Application number: 13/918,576 - Filed: 2013-06-14 - Published: 2014-07-10 - Earliest claimed: 2013-01-04 - Assignees: Place Iq. Inc. - Applicants: Place Iq. Inc. - Inventors: Stephen Milton; Duncan McCall - Web page: https://patentgrep.com/patent/US20140195530A1 ## CPC - G06F 16/9537: Spatial or temporal dependent retrieval, e.g. spatiotemporal queries - G06F 16/00: Information retrieval; Database structures therefor; File system structures therefor - G06F 16/24578: {using ranking} - G06F 16/29: Geographical information databases - G06F 16/9535: Search customisation based on user profiles and personalisation - G06Q 30/02: Marketing; Price estimation or determination; Fundraising - G06Q 30/0261: {based on user location} - H04W 4/029: Location-based management or tracking services - G06Q 30/0269: {based on user profile or attribute} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - 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 - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) ## Abstract Provided is a process of profiling a user of a mobile computing device, the process including: obtaining a location history of a user, the location history being based on signals from a mobile computing device of the user; obtaining a location-attribute score of a location identified in, or inferred from, the location history; determining, with a computer, a user-attribute score based on the location-attribute score; and storing the user-attribute score in a user-profile datastore. ## Claims ### Claim 1 A method of profiling a user of a mobile computing device, the method comprising: obtaining a location history of a user, the location history being based on signals from a mobile computing device of the user; obtaining a location-attribute score of a location identified in, or inferred from, the location history; determining, with a computer, a user-attribute score based on the location-attribute score; and storing the user-attribute score in a user-profile datastore. ### Claim 2 (depends on 1) The method of claim 1, wherein: obtaining a location-attribute score of a location comprises: mapping a location in the location history to a tile in a geographic information system (GIS), the tile being a quantization of a geographic area described by the GIS and including the location; and retrieving a list of tile-attribute scores for the tile from the GIS, the tile-attribute scores each describing a potential activity of a user while in the tile and a statistical likelihood that a user is engaging in the activity based on behavior of other users while in the tile. ### Claim 3 (depends on 1) The method of claim 1, wherein determining a user-attribute score comprises: determining a user-attribute score for a user-profile time-bin, the user profile being divided into a plurality of time-bins, with the same attribute having different values in different time-bins of the user profile, the different values corresponding to a propensity of the user to engage in an activity described by the attribute during a time within a given time-bin. ### Claim 4 (depends on 1) The method of claim 1, wherein determining a user-attribute score comprises: identifying a time-bin of a profile of the user, the time-bin corresponding to a time at which the user was at the location, the user profile having a plurality of time-bins; and determining a user-attribute score corresponding to the identified time-bin. ### Claim 5 (depends on 1) The method of claim 1, wherein obtaining a location-attribute score comprises: identifying a time-bin of a record in a GIS, the record corresponding to the location, and the time-bin corresponding to a time at which the user was at the location; and determining a user-attribute score based on an attribute score of the identified time-bin of the location. ### Claim 6 (depends on 1) The method of claim 1, wherein the location-attribute score is a time-bin specific score for the location, and wherein the user-attribute score is a time-bin specific score for the user based on the location history. ### Claim 7 (depends on 1) The method of claim 1, wherein each user is associated with a plurality of scores for the attribute, each score corresponding to a different duration of time during the week. ### Claim 8 (depends on 1) The method of claim 1, wherein obtaining a location-attribute score of a location identified in, or inferred from, the location history comprises: identifying a first tile in a GIS, the first tile defining a geographic area including the location identified in the location history. ### Claim 9 (depends on 8) The method of claim 8, wherein identifying a tile comprises: determining that the user is located in a second tile, adjacent the first tile, based on attribute scores of both the first tile and the second tile. ### Claim 10 (depends on 1) The method of claim 1, wherein obtaining a location-attribute score of a location comprises: obtaining an initial location of the user at an initial time; obtaining a subsequent location of the user at a subsequent time, the subsequent time being more than one minute after the initial time; inferring an intermediate location of the user at an intermediate time based on attributes of locations between the initial location and the subsequent location; and obtaining a location-attribute score of the intermediate location. ### Claim 11 (depends on 10) The method of claim 10, wherein the intermediate location is associated with a confidence score indicative of a likelihood that the user was at the intermediate location, and wherein the user attribute score is calculated by weighting the location-attribute score with the confidence score. ### Claim 12 (depends on 1) The method of claim 1, wherein determining a user-attribute score based on the location-attribute score comprises: calculating a measure of central tendency using the location-attribute score and scores for the attribute from previous locations of the user. ### Claim 13 (depends on 1) The method of claim 1, wherein determining a user-attribute score based on the location-attribute score comprises: determining that the location-attribute score is not an outlier relative to scores for the attribute from previous locations of the user; and in response, calculating an average of the location-attribute score and scores for the attribute from previous locations of the user. ### Claim 14 (depends on 1) The method of claim 1, wherein determining a user-attribute score based on the location-attribute score comprises: determining that adjacent locations have attribute scores consistent with the location-attribute score; and in response, calculating the user-attribute score based on the location-attribute score. ### Claim 15 (depends on 14) The method of claim 14, wherein determining that adjacent locations have attribute scores consistent with the location-attribute score comprises: determining more than a threshold amount of adjacent tiles have scores for the attribute within a threshold difference from the location-attribute score. ### Claim 16 (depends on 1) The method of claim 1, comprising: determining user-attribute scores for a plurality of attributes of a plurality of users based on location histories of the plurality of users and attributes of locations identified by the location histories; and storing the user-attribute scores in a plurality of corresponding user profiles in the user-profile datastore. ### Claim 17 (depends on 1) The method of claim 1, wherein: the location history comprises an list of geolocation records, each geolocation record including geographic coordinates expressed as a latitude and longitude and a time at which the mobile computing device was at the respective coordinates, each geolocation record being obtained by an end-user portable device having access to a location identifying service; obtaining a location-attribute score comprises: inferring locations between locations identified in the location history; for each identified or inferred location, retrieving respective tile records from a GIS, the tile records corresponding to a tile in which the respective location is disposed and adjacent tiles, each tile record corresponding to a geographic area of between 100 square meters and 100,000 square meters and being associated with one or more location-attribute scores, each location-attribute score corresponding to an activity of interest to advertisers and ordinal values indicative of a likelihood that a user is engaged in the respective activity in the tile during each of a plurality of time-bins, the time-bins defining different subsets of a week, including a weekday morning bin, a weekday lunch-time bin, and a weekend evening bin, and the attributes including the user being at work, the user engaging in sports, the user shopping, and the user engaging in tourism; determining a user-attribute score comprises: determining that location attribute scores for the tile records for the time-bin in which the user was at the location are consistent among the adjacent tiles; and in response, determining a plurality of user-attribute scores corresponding the location-attribute scores, the respective user-attribute score being an average of the corresponding location-attribute score for a time-bin including the time at which the user was a the location and previous scores for the attribute from other locations; and storing the user-attribute score comprises: storing the averaged user-attribute scores in a user profile in the user-profile datastore, user profile being stored on a tangible, non-transitory, machine-readable medium, and the user-profile datastore being operative to respond to queries from advertisers for data relevant to the selection of advertisements. ### Claim 18 (depends on 1) The method of claim 1, comprising: receiving a request from an advertiser for data about a user, the request including a user identifier; determining that the advertiser is authorized to access the user-profile datastore; retrieving from a user profile responsive to the user identifier one or more attributes of the responsive user; and sending to the advertiser data indicative of the one or more attributes. ### Claim 19 (depends on 1) The method of claim 1, comprising: obtaining user profiles of users at each of a plurality of locations corresponding to a business; and aggregating attributes of the user profiles to characterize the business. ### Claim 20 (depends on 1) The method of claim 1, comprising: obtaining a user profile of a user operating an application; and customizing the application based on the user profile. ### Claim 21 A tangible, machine-readable, non-transitory medium storing instructions that when executed by a data processing apparatus, cause the data processing apparatus to perform operations comprising: obtaining a location history of a user, the location history being based on signals from a mobile computing device of the user; obtaining a location-attribute score of a location identified in, or inferred from, the location history; determining a user-attribute score based on the location-attribute score; and storing the user-attribute score in a user-profile datastore. ### Claim 22 A system, comprising: one or more processors; and memory storing instructions that when executed by the processors cause the processors to perform operations comprising: obtaining a location history of a user, the location history being based on signals from a mobile computing device of the user; obtaining a location-attribute score of a location identified in, or inferred from, the location history; determining a user-attribute score based on the location-attribute score; and storing the user-attribute score in a user-profile datastore.