Abstract:
An initial plurality of search results is obtained based on a search query pertaining to a topic of interest. A determination is made of whether to perform clustering on the initial plurality of search results. Upon determining not to perform clustering on the search result, a user interface with the initial plurality of search results is provided. Upon determining to perform clustering on the initial plurality of search results, a user interface with a modified plurality of search results is provided. The user interface is to position a first result in the modified plurality of search results adjacent to a position of a second search result in the modified plurality of search results. The first search result is associated with a channel and the second search result is associated with the channel.
Abstract:
A system and methodology provide for annotating videos with entities and associated probabilities of existence of the entities within video frames. A computer-implemented method selects an entity from a plurality of entities identifying characteristics of a video item, where the video item has associated metadata. The computer-implemented method receives probabilities of existence of the entity in video frames of the video item, and selects a video frame determined to comprise the entity responsive to determining the video frame having a probability of existence of the entity greater than zero. The computer-implemented method determines a scaling factor for the probability of existence of the entity using the metadata of the video item, and determines an adjusted probability of existence of the entity by using the scaling factor to adjust the probability of existence of the entity. The computer-implemented method labels the video frame with the adjusted probability of existence.
Abstract:
A search result is modified to include a predetermined number of channels within a predetermined number of a plurality of entries in the search result. The search result is generated in response to a search query. The search result is modified to comprise a predetermined number of channels within a predetermined number of the plurality of entries. The modified search result is updated based on the plurality of entries and a subset of the updated modified search result is selected to be presented in response to the search query. The subset of the updated modified search result comprises the channel and at least one selection of data content.
Abstract:
A search result is modified to include a predetermined number of channels within a predetermined number of a plurality of entries in the search result. The search result is generated in response to a search query. The search result is modified to comprise a predetermined number of channels within a predetermined number of the plurality of entries. The modified search result is updated based on the plurality of entries and a subset of the updated modified search result is selected to be presented in response to the search query. The subset of the updated modified search result comprises the channel and at least one selection of data content.
Abstract:
A computer-implemented method for selecting representative frames for videos is provided. The method includes receiving a video and identifying a set of features for each of the frames of the video. The features including frame-based features and semantic features. The semantic features identifying likelihoods of semantic concepts being present as content in the frames of the video. A set of video segments for the video is subsequently generated. Each video segment includes a chronological subset of frames from the video and each frame is associated with at least one of the semantic features. The method generates a score for each frame of the subset of frames for each video segment based at least on the semantic features, and selecting a representative frame for each video segment based on the scores of the frames in the video segment. The representative frame represents and summarizes the video segment.
Abstract:
A system and methodology provide for annotating videos with entities and associated probabilities of existence of the entities within video frames. A computer-implemented method identifies an entity from a plurality of entities identifying characteristics of video items. The computer-implemented method selects a set of features correlated with the entity based on a value of a feature of a plurality of features, determines a classifier for the entity using the set of features, and determines an aggregation calibration function for the entity based on the set of features. The computer-implemented method selects a video frame from a video item, where the video frame having associated features, and determines a probability of existence of the entity based on the associated features using the classifier and the aggregation calibration function.
Abstract:
A computer system determines feature metrics for a content channel. The content channel includes one or more media items. The computer system receives a query that corresponds to a query types. The query type is associated with a subset of the feature metrics. The computer system evaluates the content channel based on the subset of feature metrics to produce a channel score for the query type and provides the channel score to position at least one of the media items of the content channel in a query result of the query.
Abstract:
An initial plurality of search results is obtained based on a search query pertaining to a topic of interest. A determination is made of whether to perform clustering on the initial plurality of search results. Upon determining not to perform clustering on the search result, a user interface with the initial plurality of search results is provided. Upon determining to perform clustering on the initial plurality of search results, a user interface with a modified plurality of search results is provided. The user interface is to position a first result in the modified plurality of search results adjacent to a position of a second search result in the modified plurality of search results. The first search result is associated with a channel and the second search result is associated with the channel.
Abstract:
A search result is modified to include a predetermined number of channels within a predetermined number of a plurality of entries in the search result. The search result is generated in response to a search query. The search result is modified to comprise a predetermined number of channels within a predetermined number of the plurality of entries. The modified search result is updated based on the plurality of entries and a subset of the updated modified search result is selected to be presented in response to the search query. The subset of the updated modified search result comprises the channel and at least one selection of data content.
Abstract:
A system and methodology provide for annotating videos with entities and associated probabilities of existence of the entities within video frames. A computer-implemented method identifies an entity from a plurality of entities identifying characteristics of video items. The computer-implemented method selects a set of features correlated with the entity based on a value of a feature of a plurality of features, determines a classifier for the entity using the set of features, and determines an aggregation calibration function for the entity based on the set of features. The computer-implemented method selects a video frame from a video item, where the video frame having associated features, and determines a probability of existence of the entity based on the associated features using the classifier and the aggregation calibration function.