APP RECOMMENDATION USING CROWD-SOURCED LOCALIZED APP USAGE DATA
First Claim
1. A method comprising:
- receiving, at an application recommendation system, a plurality of app usage records from a plurality of mobile devices, wherein the plurality of app usage records each comprise an application identifier corresponding to an application, a usage location corresponding to an execution of the application, and a usage timestamp corresponding to an execution of the application;
analyzing, by the application recommendation system, the plurality of app usage records to;
determine the app usage records for a first application; and
for each of one or more locations;
calculate a statistical value measuring a localized usage at the respective location relative to other locations;
compare the statistical value to a threshold; and
use respective locations when the statistical value exceeds the threshold to identify one or more hotspots of the first application.
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Accused Products
Abstract
Apps may be tagged with location data when they are used. Mobile device may anonymously submit app usage data. Aggregated app usage data from many mobile devices may be analyzed to determine apps that are particularly relevant to a given location (i.e., exhibiting a high degree of localization). Analysis may include determining the app usage intensity, whether hotspots exist or not at a given location, the spatial entropy of a particular app, the device populations in a particular area, etc. Based on the localized app analysis, apps may be ranked according to local relevance, and, based on this ranking, app recommendations may be provided to a user.
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Citations
20 Claims
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1. A method comprising:
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receiving, at an application recommendation system, a plurality of app usage records from a plurality of mobile devices, wherein the plurality of app usage records each comprise an application identifier corresponding to an application, a usage location corresponding to an execution of the application, and a usage timestamp corresponding to an execution of the application; analyzing, by the application recommendation system, the plurality of app usage records to; determine the app usage records for a first application; and for each of one or more locations; calculate a statistical value measuring a localized usage at the respective location relative to other locations; compare the statistical value to a threshold; and use respective locations when the statistical value exceeds the threshold to identify one or more hotspots of the first application. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method of partitioning a domain of interest comprising:
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receiving, at a server, a plurality of location records each comprising a location and a timestamp from a plurality of mobile devices; analyzing, by the server, the plurality of location records to determine a device population over the domain of interest; and based on device population, partitioning the domain of interest into non-uniform regions based on device population. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15)
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16. A computer readable storage medium having program code stored thereon, the program code including instructions that, when executed by a processor in a device, cause the processor to execute a method comprising:
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receiving a plurality of usage records each comprising a location and a timestamp from a plurality of mobile devices; analyzing the plurality of usage records to determine a device population over the domain of interest; detecting device population hotspots; and partitioning the domain of interest into non-uniform regions based on device population hotspots. - View Dependent Claims (17, 18, 19, 20)
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Specification