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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 co

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.

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1. A non-transitory computer storage medium storing instructions configured to instruct a computing device to perform a method, the method comprising: receiving, for a mobile device, input data identifying: a plurality of time instances in a period of time; anda plurality of locations of the mobile

1. A non-transitory computer storage medium storing instructions configured to instruct a computing device to perform a method, the method comprising: receiving, for a mobile device, input data identifying: a plurality of time instances in a period of time; anda plurality of locations of the mobile device at the plurality of time instances respectively; andidentifying, by the computing device from the input data, a location of a home of a user of the mobile device, by: identifying a plurality of regions, each of the regions having a predefined boundary and containing at least one of the plurality of locations of the mobile device;identifying a plurality of visitation types for the plurality of time instances of the mobile device being at the plurality of locations;computing, for each respective region in the plurality of regions, a plurality of visitation frequencies corresponding to the plurality of visitation types respectively;computing, for the respective region, a score based at least in part on the plurality of visitation frequencies, wherein the plurality of regions have a plurality of scores respectively; andselecting, from the plurality of region candidates and based on the plurality of scores, a home region as the home of the user. 2. The non-transitory computer storage medium of claim 1, wherein the identifying of the plurality of regions includes: identifying, for each respective location in the plurality of locations, a respective region that contains the respective location, by: storing cell data associating a set of cell identifiers with a set of regions, wherein each respective cell identifier in the set of cell identifiers is stored in association with a region that contains locations that are convertible to the respective cell identifier;converting the respective location to a particular cell identifier; andidentifying, as the respective region that contains the respective location, a region that is stored in association with the particular cell identifier in the cell data. 3. The non-transitory computer storage medium of claim 2, wherein cells identified by the set of cell identifiers are in a hierarchical grid system having grid lines aligned with numbers of digits of precision in longitudinal and latitudinal coordinates on the earth. 4. The non-transitory computer storage medium of claim 1, wherein the score is based on a weight determined based on recency of locations of the mobile device in the respective region. 5. The non-transitory computer storage medium of claim 1, wherein the score is based on a weight determined based on a total number of different regions that contain the locations of the mobile device. 6. The non-transitory computer storage medium 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 user of the mobile device. 7. The non-transitory computer storage medium of claim 1, wherein the predefined boundary is a parcel boundary of land in residential areas. 8. The non-transitory computer storage medium of claim 7, further comprising: breaking a tie in the plurality of scores based on visitations to an area of a predetermined width surrounding but not within a boundary of each respective region that has the tie. 9. The non-transitory computer storage medium of claim 1, wherein the method further comprises: determining, by the computing device, a count of different mobile devices having location in each of the regions during the period of time;wherein the selecting of the home region is further based on the count of different mobile devices having locations in each of the regions. 10. The non-transitory computer storage medium of claim 9, wherein the selecting of the home region includes: identifying a set of region candidates, wherein each of the region candidates has a count of different mobile devices that is less than a predetermined threshold during the period of time; andselecting the home region from the set of region candidates based on the scores. 11. A method implemented in a computing device, the method comprising: receiving, for a mobile device, input data identifying: a plurality of time instances in a period of time; anda plurality of locations of the mobile device at the plurality of time instances respectively; andidentifying, by the computing device from the input data, a location of a home of a user of the mobile device, by: identifying a plurality of regions, each of the regions having a predefined boundary and containing at least one of the plurality of locations of the mobile device;identifying a plurality of visitation types for the plurality of time instances of the mobile device being at the plurality of locations;computing, for each respective region in the plurality of regions, a plurality of visitation frequencies corresponding to the plurality of visitation types respectively;computing, for the respective region, a score based at least in part on the plurality of visitation frequencies, wherein the plurality of regions have a plurality of scores respectively; andselecting, from the plurality of region candidates and based on the plurality of scores, a home region as the home of the user. 12. The method of claim 11, wherein the identifying of the plurality of regions includes: identifying, for each respective location in the plurality of locations, a respective region that contains the respective location, by: storing cell data associating a set of cell identifiers with a set of regions, wherein each respective cell identifier in the set of cell identifiers is stored in association with a region that contains locations that are convertible to the respective cell identifier;converting the respective location to a particular cell identifier; andidentifying, as the respective region that contains the respective location, a region that is stored in association with the particular cell identifier in the cell data. 13. The method of claim 12, wherein each region in the set of regions has a predefined boundary that is a parcel boundary of land in a residential area. 14. The method of claim 13, further comprising: determining, by the computing device, a count of different mobile devices having location in each of the regions during the period of time;wherein the selecting of the home region is further based on the count of different mobile devices having locations in each of the regions. 15. The method of claim 14, wherein the selecting of the home region includes: identifying a set of region candidates, wherein each of the region candidates has a count of different mobile devices that is less than a predetermined threshold during the period of time; andselecting the home region from the set of region candidates based on the scores. 16. The method of claim 13, wherein the plurality of visitation types include at least one of: visitations outside of working hours; andvisitations in weekends. 17. A computing device, comprising: at least one microprocessor; andmemory storing instructions configured to instruct the at least one microprocessor to: store, for a mobile device, data identifying: a plurality of time instances in a period of time; anda plurality of locations of the mobile device at the plurality of time instances respectively; andidentify, by the computing device from the data, a location of a home of a user of the mobile device, by: identifying a plurality of regions, each of the regions having a predefined boundary and containing at least one of the plurality of locations of the mobile device;identifying a plurality of visitation types for the plurality of time instances of the mobile device being at the plurality of locations;computing, for each respective region in the plurality of regions, a plurality of visitation frequencies corresponding to the plurality of visitation types respectively;computing, for the respective region, a score based at least in part on the plurality of visitation frequencies, wherein the plurality of regions have a plurality of scores respectively; andselecting, from the plurality of region candidates and based on the plurality of scores, a home region as the home of the user. 18. The computing device of claim 17, wherein each of the visitation type is based on a characteristic of a time instance of a location of the mobile device. 19. The computing device of claim 18, wherein the characteristic is being outside of working hours. 20. The computing device of claim 18, wherein the characteristic is being in weekends.