Systems and methods to identify home addresses of mobile devices

• US 9,503,863 B2
• Filed: 02/03/2016
• Issued: 11/22/2016
• Est. Priority Date: 01/09/2015
• Status: Active Grant

• Current Assignee: InMarket Media, LLC
• Original Assignee: NinthDecimal, Inc. (InMarket Media, LLC)
• Inventors: Rose, Elena, Dixon, Mark Christopher, Ching, Kevin Toshio, Milenkiy, Veronica
• Primary Examiner(s): PATEL, DHAVAL V
• Application Number:
  US15/014,943
• Publication Number:
  US 20160205510A1
• Time in Patent Office: 293 Days
• Field of Search: 455/404.2, 455/406, 455/456.1, 707/724, 707/737, 707/746
• US Class Current: 1/1
• CPC Class Codes: G01S 5/0027 of actual mobile position, i.e. position determined on mobile
• CPC Class Codes: G01S 5/0252 Radio frequency fingerprinting
• CPC Class Codes: G01S 5/0295 Proximity-based methods, e.g. position inferred from reception of particular signals
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: H04W 4/025 using location based information parameters
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management
• CPC Class Codes: H04W 8/02 Processing of mobility data, e.g. registration information at HLR [Home Location Register] or VLR [Visitor Location Register]; Transfer of mobility data, e.g. between HLR, VLR or external networks
• CPC Class Codes: H04W 8/10 between location register and external networks
• CPC Class Codes: H04W 8/18 Processing of user or subscriber data, e.g. subscribed services, user preferences or user profiles; Transfer of user or subscriber data

Abstract

Systems and methods including a database storing the identifiers of cells representing residential parcels of real estate properties. Mobile devices determine the coordinates of their locations during a period of time using a location determination system, such as a global positioning system. The coordinates are converted to cell identifiers to look up corresponding residential parcels that have been visited by the mobile devices. A server generates a visitation data set for each residential parcel visited by each mobile device, including different types of frequencies of the mobile device visiting the residential parcel (e.g., night, weekend). A server filters the residential parcels based on visitation frequencies to identify home candidates and then further filters the home candidates based on the count of mobile devices having the home candidates. A home parcel, and thus its address, is identified from the filtered home candidate(s) for each mobile device.

Claims

1. A method implemented in a computing device, the method comprising:

receiving, in the computing device, data identifying a set of location instances in a period of time, each respective location instance of the location instances identifying;

a mobile device,

a location of the mobile device, and

a timestamp of the location of the mobile device in the period of time; and

determining, by the computing device, a home of each respective mobile device by;

identifying, by the computing device, a set of regions in which the location instances are located;

computing, by the computing device, a visitation dataset for each respective region visited by the respective mobile device, wherein the visitation dataset identifies a plurality of frequencies of visitations of different types;

filtering, by the computing device, regions visited by the respective mobile device to identify one or more region candidates; and

in response to a determination that the respective mobile device has more than one region candidate resulting from the filtering,

computing, by the computing device from the visitation dataset, a score for each of the more than one region candidate; and

selecting, from the more than one region candidate and by the computing device according to the computed score, the home of the respective mobile device.

2. The method of claim 1, wherein the score is based on a count of different days of location instances of the respective mobile device that are located within the respective region but have timestamps outside working hours.

3. The method of claim 1, wherein the score is based on a count of different days of location instances of the respective mobile device that are located within the respective region and have timestamps in weekends.

4. The method of claim 1, wherein the score is based on a weight determined based on recency of location instances of the respective mobile device in the respective region.

5. The method of claim 1, wherein the score is based on a weight determined based on a total number of different regions that have location instances of the respective mobile device.

6. The method of claim 1, wherein the score is based on a weight determined based on whether the respective region has been previously identified as the home of the mobile device.

7. The method of claim 1, wherein the set of regions are limited to and defined by parcel boundaries of land in residential areas;

and the method further comprises;

breaking a tie in the score based on visitations to an area of a predetermined width surrounding a boundary of each respective residential region but not within boundaries of residential regions.

8. The method of claim 7, further comprising:

storing a set of cell identifiers of a hierarchical grid system having grid lines aligned with numbers of digits of precision in longitudinal and latitudinal coordinates on the earth, including store each respective cell identifier of the set of cell identifiers in association with a set of region identifiers identifying one or more regions that are at least partially in a cell identified by the respective cell identifier;

wherein the identifying of the set of regions in which the location instances are located includes, for the respective location instance in the set of location instances in the period of time;

converting to a cell identifier the location of the mobile device identified in the respective location instance;

searching in the set of cell identifiers for a match of the cell identifier converted from the location of the mobile device identified in the respective location instance;

retrieving a set of region identifiers associated with the match identified via the searching; and

identifying the respective location instance as being within one or more regions identified by the set of region identifiers retrieved via the searching.

9. The method of claim 1, wherein the visitation dataset includes:

a count of different days of location instances of the respective mobile device located within the respective region;

a count of different days of location instances of the respective mobile device that are located within the respective region and have timestamps in night hours; and

a count of different days of location instances of the respective mobile device that are located within the respective region and have timestamps in weekends.

10. The method of claim 9, wherein the night hours are between 7 pm to 8 am of a day;

and the weekends are Saturdays and Sundays.

11. The method of claim 9, wherein the filtering is based on a threshold computed based at least in part on:

a count of location instances of different mobile devices located in the respective region; and

a count of different mobile devices of location instances located in the respective region.

12. The method of claim 11, wherein in response to a determination that the filtering produces no region candidate for the respective mobile device, relaxing a criterion of the filtering.

13. The method of claim 11, wherein the threshold is computed based further on an average count of different mobile devices of location instances located in the respective region and neighboring regions of the respective region.

14. The method of claim 11, wherein the respective region is not selected as a region candidate when the threshold is higher than both

the count of different days of location instances of the respective mobile device that are located within the respective region but have timestamps in night hours;

and

the count of different days of location instances of the respective mobile device that are located within the respective region but have timestamps in weekends.

15. The method of claim 1, further comprising:

determining, by the computing device, a count of different mobile devices having location instances in each of the regions;

wherein the selecting of the home of the respective mobile device is further based on the count of different mobile devices having location instances in each of the regions.

16. The method of claim 15, wherein the selecting of the home of the respective mobile device includes:

identifying a first subset of the one or more region candidates, wherein each region candidate in the first subset having a count of different mobile devices less than a first threshold; and

selecting the home of the respective mobile device from the first subset based on the score.

17. The method of claim 16, wherein the selecting of the home of the respective mobile device further includes, in response to a determination that the first subset is empty:

identifying a second subset of the one or more region candidates, wherein each region candidate in the second subset having a count of different mobile devices less than a second threshold greater than the first threshold; and

selecting the home of the respective mobile device from the second subset based on the score.

18. A non-transitory computer storage medium storing instructions configured to instruct a computing device to perform a method, the method comprising:

receiving, in the computing device, data identifying a set of location instances in a period of time, each respective location instance of the location instances identifying;

a mobile device,

a location of the mobile device, and

a timestamp of the location of the mobile device in the period of time; and

determining, by the computing device, a home of each respective mobile device by;

identifying, by the computing device, a set of regions in which the location instances are located;

computing, by the computing device, a visitation dataset for each respective region visited by the respective mobile device, wherein the visitation dataset identifies a plurality of frequencies of visitations of different types;

filtering, by the computing device, regions visited by the respective mobile device to identify one or more region candidates; and

in response to a determination that the respective mobile device has more than one region candidate resulting from the filtering,

computing, by the computing device from the visitation dataset, a score for each of the more than one region candidate; and

selecting, from the more than one region candidate and by the computing device according to the computed score, the home of the respective mobile device.

19. A computing device, comprising:

at least one microprocessor; and

memory storing instructions configured to instruct the at least one microprocessor to;

receive, in the computing device, data identifying a set of location instances in a period of time, each respective location instance of the location instances identifying a mobile device, a location of the mobile device, and a timestamp of the location of the mobile device in the period of time;

determine, by the computing device, a home of each respective mobile device by;

identifying, by the computing device, a set of regions in which the location instances are located;

computing, by the computing device, a visitation dataset for each respective region visited by the respective mobile device, wherein the visitation dataset identifies a plurality of frequencies of visitations of different types;

filtering, by the computing device, regions visited by the respective mobile device to identify one or more region candidates; and

in response to a determination that the respective mobile device has more than one region candidate resulting from the filtering,

computing, by the computing device from the visitation dataset, a score for each of the more than one region candidate; and

selecting, from the more than one region candidate and by the computing device according to the computed score, the home of the respective mobile device.