System and method for logistic matrix factorization of implicit feedback data, and application to media environments
First Claim
1. A system for use of logistic matrix factorization of implicit feedback data in determination and communication of media content item recommendations, comprising:
- one or more computers, each of which includes a processor and a memory, and a media server provided thereon that includes access points that receive requests from media devices to access media content at the media server;
wherein in response to receiving, via the access points, the requests from the media devices to access the media content at the media server, the media server collects a usage data describing usage by a plurality of users, of a plurality of media content items, wherein the usage data is provided as an observation matrix, wherein each entry in the observation matrix represents a number of times that a particular user of a media device has interacted with a particular media content item;
a data collection and aggregation processor that applies a logistic function to determine latent factors that indicate a likelihood of particular users to prefer particular media content items, includingfactorizing the observation matrix of usage data by lower-dimensional matrices representing, respectively a user'"'"'s taste, and a media content item'"'"'s implicit characteristics, anddetermining one or more probabilities that the particular users will interact with the particular media content items; and
wherein the media server, for a particular user of a media device;
receives an indication of the latent factors that indicate the likelihood of the particular users to prefer the particular media content items,determines, for the particular user, recommended media content items, based on the latent factors, andcommunicates an indication of the recommended media content items to the particular user'"'"'s media device.
3 Assignments
0 Petitions
Accused Products
Abstract
In accordance with an embodiment, described herein is a system and method for logistic matrix factorization of implicit feedback data, with application to media environments or streaming services. While users interact with an environment or service, for example a music streaming service, usage data reflecting implicit feedback can be collected in an observation matrix. A logistic function can be used to determine latent factors that indicate whether particular users are likely to prefer particular items. Exemplary use cases include providing personalized recommendations, such as personalized music recommendations, or generating playlists of popular artists.
-
Citations
20 Claims
-
1. A system for use of logistic matrix factorization of implicit feedback data in determination and communication of media content item recommendations, comprising:
-
one or more computers, each of which includes a processor and a memory, and a media server provided thereon that includes access points that receive requests from media devices to access media content at the media server; wherein in response to receiving, via the access points, the requests from the media devices to access the media content at the media server, the media server collects a usage data describing usage by a plurality of users, of a plurality of media content items, wherein the usage data is provided as an observation matrix, wherein each entry in the observation matrix represents a number of times that a particular user of a media device has interacted with a particular media content item; a data collection and aggregation processor that applies a logistic function to determine latent factors that indicate a likelihood of particular users to prefer particular media content items, including factorizing the observation matrix of usage data by lower-dimensional matrices representing, respectively a user'"'"'s taste, and a media content item'"'"'s implicit characteristics, and determining one or more probabilities that the particular users will interact with the particular media content items; and wherein the media server, for a particular user of a media device; receives an indication of the latent factors that indicate the likelihood of the particular users to prefer the particular media content items, determines, for the particular user, recommended media content items, based on the latent factors, and communicates an indication of the recommended media content items to the particular user'"'"'s media device. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
-
-
10. A method for use of logistic matrix factorization of implicit feedback data in determining and communicating media content item recommendations, comprising:
-
providing, at one or more computers, each of which includes a processor and a memory, a media server that includes access points that receive requests from media devices to access media content at the media server; in response to receiving, via the access points, the requests from the media devices to access the media content at the media server, collecting by the media server a usage data describing usage by a plurality of users, of a plurality of media content items, wherein the usage data is provided as an observation matrix, wherein each entry in the observation matrix represents a number of times that a particular user of a media device has interacted with a particular media content item; processing the observation matrix including the usage data by a data collection and aggregation processor, including applying a logistic function to determine latent factors that indicate a likelihood of particular users to prefer particular media content items, including factorizing the observation matrix of usage data by lower-dimensional matrices representing, respectively a user'"'"'s taste, and a media content item'"'"'s implicit characteristics, and determining one or more probabilities that the particular users will interact with the particular media content items; receiving at the media server an indication of the latent factors that indicate the likelihood of the particular users to prefer the particular media content items; determining, for a particular user, recommended media content, based on the latent factors; and communicating an indication of the recommended media content items to the particular user'"'"'s media device. - View Dependent Claims (11, 12, 13, 14, 15)
-
-
16. A non-transitory computer readable storage medium, including instructions stored thereon which when read and executed by one or more computers cause the one or more computers to perform the method comprising:
-
providing, at one or more computers, each of which includes a processor and a memory, a media server that includes access points that receive requests from media devices to access media content at the media server; in response to receiving, via the access points, the requests from the media devices to access the media content at the media server, collecting by the media server a usage data describing usage by a plurality of users, of a plurality of media content items, wherein the usage data is provided as an observation matrix, wherein each entry in the observation matrix represents a number of times that a particular user of a media device has interacted with a particular media content item; processing the observation matrix including the usage data by a data collection and aggregation processor, including applying a logistic function to determine latent factors that indicate a likelihood of particular users to prefer particular media content items, including factorizing the observation matrix of usage data by lower-dimensional matrices representing, respectively a user'"'"'s taste, and a media content item'"'"'s implicit characteristics, and determining one or more probabilities that the particular users will interact with the particular media content items; receiving at the media server an indication of the latent factors that indicate the likelihood of the particular users to prefer the particular media content items; determining, for a particular user, recommended media content, based on the latent factors; and communicating an indication of the recommended media content items to the particular user'"'"'s media device. - View Dependent Claims (17, 18, 19, 20)
-
Specification