Piksel, Inc.

Kit Digital Inc.

Peerset, Inc.

Issar Amit Kanigsberg

Daniel Marc Veidlinger

Myer Joshua Mozersky

Philip Antony Shaw

Tamer El Shazli

Ralf Wilhelm Tillmann

Andrew David Gayter

Miles Eusebius Weaver

A computer-implemented method of triggering an action based on behaviour of a user consuming content at a user device, the method comprising receiving content change signals at a processor executing a content change detection algorithm, wherein the content change signals denote a change of content on the user device; wherein the detection algorithm compares the content change signals with a content change behaviour associated with that device to detect a surfing condition and generates a triggering control signal for triggering an action when the surfing condition for that device is detected.

Triggering an action in a computer device

A content delivery system delivers media content to a content consuming user and comprises computer storage storing a media asset; an analysis component configured to perform an analysis of the user's behavior at a user device to infer a desirable attribute of a modified version of the media asset, the user's behavior comprising the user instigating at the user device requests for content other than the media asset to a computer network, and consuming the requested other content when returned from the network. The requests do not explicitly identify the desirable attribute. The system comprises a modified version generation component configured to receive the media asset and modify the media asset based on the analysis of the user's behavior; and a content delivery component configured to supply the modified version of the media asset to a media output device of the user, the modified version exhibiting the desirable attribute.

Delivering media content

In the following, a content delivery system delivers a modified version of a media asset to a current content consuming user. Control information identifying a desired attribute of the modified version of the asset is received from the current content consuming user. The media asset is modified based on the control information and audience reaction data associated with the media asset and generated by analyzing at least a previous content consuming user's reactions to the media asset while the media asset was supplied to a media output device of the previous content consuming user.

Content delivery system for key moment identification from audience data

A search technology generates recommendations with minimal user data and participation, and provides better interpretation of user data, such as popularity, thus obtaining breadth and quality in recommendations. It is sensitive to the semantic content of natural language terms and lets users briefly describe the intended recipient (i.e., interests, eccentricities, previously successful gifts). Based on that input, the recommendation software system and method determines the meaning of the entered terms and creatively discover connections to gift recommendations from the vast array of possibilities. The user may then make a selection from these recommendations. The search/recommendation engine allows the user to find gifts through connections that are not limited to previously available information on the Internet. Thus, interests can be connected to buying behavior by relating terms to respective items.

Recommendation systems and methods using interest correlation

In the following, a content delivery system delivers a modified version of a media asset to a current content consuming user. Control information identifying a desired attribute of the modified version of the asset is received from the current content consuming user. The media asset is modified based on the control information and audience reaction data associated with the media asset and generated by analyzing at least a previous content consuming user's reactions to the media asset whilst the media asset was supplied to a media output device of the previous content consuming user.

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Mill Valley, CA, United States of America

Issar Amit Kanigsberg