Personalized recommendations based on related users
First Claim
1. A computer-implemented method of recommending computer applications, the method comprising:
- selecting a target user of an application distribution system for which to generate recommendations;
identifying one or more related users of the target user;
identifying first applications accessed by installed on first devices of the one or more related users;
identifying usage characteristics of the first applications, the one or more usage characteristics reflecting usage of the first applications subsequent to installation of the first applications on the first devices by the one or more related users, wherein the usage characteristics comprise the following;
a frequency of usage associated with the first applications, a time of usage associated with the first applications, and a location of usage associated with the first applications; and
selecting one or more second applications as recommendations for the target user based at least partly on the usage characteristics, said selecting comprising selecting one or more related applications that have usage associations with the first applications, and wherein said selecting the one or more second applications comprises selecting a most highly-ranked subset of the first applications based at least in part on the usage characteristics;
wherein at least said selecting is implemented by one or more processors.
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Accused Products
Abstract
This disclosure describes systems and associated processes for generating recommendations for users based on usage, among other things. These systems and processes are described in the context of an interactive computing system that enables users to download applications for mobile devices (such as phones) or for other computing devices. Users'"'"' interactions with applications once they are downloaded can be observed and tracked, with such usage data being collected and provided to the interactive computing system. The interactive computing system can include a recommendation system or service that processes the usage data from a plurality of users to detect usage patterns. Using these usage patterns, among possibly other data, such as data about related users'"'"' applications, the recommendation system can recommend applications to users for download.
149 Citations
14 Claims
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1. A computer-implemented method of recommending computer applications, the method comprising:
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selecting a target user of an application distribution system for which to generate recommendations; identifying one or more related users of the target user; identifying first applications accessed by installed on first devices of the one or more related users; identifying usage characteristics of the first applications, the one or more usage characteristics reflecting usage of the first applications subsequent to installation of the first applications on the first devices by the one or more related users, wherein the usage characteristics comprise the following;
a frequency of usage associated with the first applications, a time of usage associated with the first applications, and a location of usage associated with the first applications; andselecting one or more second applications as recommendations for the target user based at least partly on the usage characteristics, said selecting comprising selecting one or more related applications that have usage associations with the first applications, and wherein said selecting the one or more second applications comprises selecting a most highly-ranked subset of the first applications based at least in part on the usage characteristics; wherein at least said selecting is implemented by one or more processors. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A Non-transitory physical computer storage comprising computer-executable instructions configured to implement a method of recommending computer applications, the method comprising:
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selecting a target user of an application distribution system for which to generate recommendations; identifying one or more related users of the target user; identifying first applications accessed by installed on first devices of the one or more related users; identifying usage characteristics of the first applications, the one or more usage characteristics reflecting usage of the first applications subsequent to installation of the first applications on the first devices by the one or more related users, wherein the usage characteristics comprise the following;
a frequency of usage associated with the first applications, a time of usage associated with the first applications, and a location of usage associated with the first applications; andselecting one or more second applications as recommendations for the target user based at least partly on the identified first applications, said selecting comprising selecting one or more related applications that have usage associations with the first applications, and wherein said selecting the one or more second applications comprises selecting a most highly-ranked subset of the first applications based at least in part on the usage characteristics. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A system for recommending computer applications, the system comprising:
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an application distribution service configured to provide applications for download by a plurality of user computing systems; and a recommendation service comprising computer hardware configured to implement a social recommender, the social recommender configured to; select a target user of an application distribution system for which to generate recommendations; identify one or more related users of the target user; identify first applications accessed by installed on first devices of the one or more related users; identify usage characteristics of the first applications, the usage characteristics reflecting usage of the first applications subsequent to installation of the first applications on the first devices by the one or more related users; and select one or more second applications as recommendations for the target user based at least partly on usage characteristics, by at least selecting one or more related applications that have usage associations with the first applications, wherein the social recommender is further configured to select the one or more second applications by at least selecting a most highly-ranked subset of the first applications based at least in part on the usage characteristics. - View Dependent Claims (14)
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Specification