Netflix Inc.

Satish Kumar Krishnamurthy

Neil D Hunt

John Funge

Jonathan Michael Sanders

Christopher Francis Pouliot

Todd Scot Yellin

Carlos Alberto Gomez Uribe

Eric Lucas

One embodiment of the invention sets forth a mechanism for identifying similar items within a plurality of items available to a group of users. The mechanism includes identifying a first count that indicates a number of times any user has interacted with a first item included in the plurality of items and subsequently with any other item, identifying a second count that indicates a number of times any user within the has interacted with a second item included in the plurality of items after interacting with the first item, computing a probability that indicates the likelihood of a particular user interacting with the second item after interacting with the first item based on the first count and the second count, and computing a similarity score that indicates the similarity between the first item and the second item based on the probability and a popularity score associated with the second item.

Identifying similar items based on interaction history

One embodiment of the present invention sets forth a technique for recommending digital content to a user of a digital content application based on continually learned patterns of behavior. Based on metrics collected from a current session of the digital content application, properties associated with one or more users interacting with the application are inferred. The inferred properties are matched against previously defined patterns of behavior to identify digital content that could be presented to the one or more users for optional selection.

Recommending digital content based on implicit user identification

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Los Gatos, CA, United States of America

Satish Kumar Krishnamurthy