Abstract:
In one example, a method includes receiving, by a computing device, an indication of a detected force applied to the computing device. The method further comprises determining, by the computing device, that the detected force matches a corresponding input that the computing device associates with a corresponding function that is executable by the computing device. The method further comprises generating, by the computing device and in response to determining that the detected force matches the corresponding input and, a non-visual output based on the corresponding function.
Abstract:
In one example, a method includes receiving, by a computing device, an indication of a detected force applied to the computing device. The method further comprises determining, by the computing device, that the detected force matches a corresponding input that the computing device associates with a corresponding function that is executable by the computing device. The method further comprises generating, by the computing device and in response to determining that the detected force matches the corresponding input and, a non-visual output based on the corresponding function.
Abstract:
In one example, a method includes receiving, by a computing device, an indication of a detected force applied to the computing device. The method further comprises determining, by the computing device, that the detected force matches a corresponding input that the computing device associates with a corresponding function that is executable by the computing device. The method further comprises generating, by the computing device and in response to determining that the detected force matches the corresponding input and, a non-visual output based on the corresponding function.
Abstract:
A method, computer program product, and system is described. A group including a plurality of individuals is defined based upon, at least in part, participation of the plurality of individuals in one or more consumption sessions. A group profile is designated for the group. Consumption of a first item of content by a portion of the group during a consumption session participated in by at least the portion of the group is identified. An indicator associated with the first item of content consumed by the portion of the group during the consumption session is associated with the group profile. A recommendation of a second item of content is provided to one or more members of the group, wherein the recommendation is based upon, at least in part, associating with the group profile the indicator associated with the first item of content.
Abstract:
User engagement in unwatched videos is predicted by collecting and aggregating data describing user engagement with watched videos. The data are normalized to reduce the influence of factors other than the content of the videos on user engagement. Engagement metrics are calculated for segments of watched videos that indicate user engagement with each segment relative to overall user engagement with the watched videos. Features of the watched videos within time windows are characterized, and a function is learned that relates the features of the videos within the time windows to the engagement metrics for the time windows. The features of a time window of an unwatched video are characterized, and the learned function is applied to the features to predict user engagement to the time window of the unwatched video. The unwatched video can be enhanced based on the predicted user engagement.
Abstract:
The subject matter of this specification can be implemented in, among other things, a method for refining search results. The method includes a step for receiving a request to refine search results, wherein the request identifies a first social circle to apply for refining the search results, wherein the first social circle comprises a preset group of contacts of a user within a social network service. The method also includes a step for retrieving search results based on the received request and a step for refining the retrieved search results based on the identified first social circle. The method also includes a step for providing at least a portion of the refined search results to an electronic device for display.
Abstract:
The disclosure includes a system and method for recommending multi-party communication sessions. The system includes: a user model module, a content model module and a determination module. The user model module determines a user social interest model based at least in part on user profile data. The content data module determines interest data describing content data associated with one or more content identifiers. The content model module determines one or more content models describing the content data. The determination module determines whether a match exists between the user social interest model and the one or more content models. The determination module determines the one or more multi-party communication sessions for the recommendation responsive to determining the match exists between the user social interest model and the one or more content models.
Abstract:
A video hosting web site receives uploaded video content and processes the video to determine ad surfaces. The ad surfaces comprise spatio-temporal regions of the video suitable for placement of advertisement such as background surfaces or other regions of low interest. The uploaded video and ad surfaces are stored to a video database that is accessible to viewers visiting the video hosting web site. When a shared video is requested, the video hosting site provides the requested video content together with the ad surfaces and advertisements. The advertisements are blended with the ad surfaces in the video at playtime so that the advertisements appear as part of the video scene. This allows the video hosting web site to present advertisements to the viewer without significantly distracting the viewer from the requested content.
Abstract:
A system and method is disclosed for organizing search results in response to a search query. A search query and sorting criteria are received from a web browser, the sorting criteria including a coarse level of granularity and a fine level of granularity. Results are received from a search engine based on the search query and the search results are organized based on the multiple sorting criteria. In this regard, the search results are ordered top-down from the coarse level of granularity to the fine level of a granularity. The organized search results are then provided for display to the web browser.
Abstract:
A highlight learning technique is provided to detect and identify highlights in sports videos. A set of event models are calculated from low-level frame information of the sports videos to identify recurring events within the videos. The event models are used to characterize videos by detecting events within the videos and using the detected events to generate an event vector. The event vector is used to train a classifier to identify the videos as highlight or non-highlight.