Identifying presentation styles of educational videos
First Claim
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1. A system for training a video presentation style classifier, comprising:
- one or more computing devices, said computing devices being in communication with each other via a computer network whenever there is a plurality of computing devices; and
a computer program having program modules executable by the one or more computing devices, the one or more computing devices being directed by the program modules of the computer program to;
receive a training dataset comprising a plurality of videos each of which is labeled with a presentation style identifier specifying the presentation style that is predominately employed in the video, said specified presentation style being a one of the presentation styles in a set of possible presentation styles;
use the training dataset to independently learn a different classifier for each possible unordered pair of presentation styles in the set of possible presentation styles; and
combine the different classifiers using probabilistic fusion, said combination producing the video presentation style classifier.
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Abstract
The presentation style of a video is identified. A set of features that represents the video is computed. A pre-learned video presentation style classifier is then used to weight each of the features in the set of features and determine a presentation style that is predominately employed in the video based on the weighting of the features.
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Citations
20 Claims
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1. A system for training a video presentation style classifier, comprising:
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one or more computing devices, said computing devices being in communication with each other via a computer network whenever there is a plurality of computing devices; and a computer program having program modules executable by the one or more computing devices, the one or more computing devices being directed by the program modules of the computer program to; receive a training dataset comprising a plurality of videos each of which is labeled with a presentation style identifier specifying the presentation style that is predominately employed in the video, said specified presentation style being a one of the presentation styles in a set of possible presentation styles; use the training dataset to independently learn a different classifier for each possible unordered pair of presentation styles in the set of possible presentation styles; and combine the different classifiers using probabilistic fusion, said combination producing the video presentation style classifier. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A computer-implemented process for allowing a user to search for videos, comprising the actions of:
using one or more computing devices that are in communication with each other via a computer network to perform the following process actions; implicitly learning the presentation style preferences of the user, said implicit learning comprising; for each video that the user views, computing a set of features that represents the video, and using a pre-learned video presentation style classifier to weight each of the features in said set and determine a presentation style that is predominately employed in the video, said presentation style determination being based on the weighting of said features; receiving a user video query; submitting the user video query to a search engine; receiving search results for the user video query from the search engine; and whenever the user video query does not explicitly specify one or more particular presentation styles the user is interested in, using the learned presentation style preferences of the user to refine the search results, and providing the refined search results to the user. - View Dependent Claims (8, 9, 10)
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11. A computer-implemented process for training a video presentation style classifier, comprising the actions of:
using one or more computing devices that are in communication with each other via a computer network to perform the following process actions; receiving a training dataset comprising a plurality of videos each of which is labeled with a presentation style identifier specifying the presentation style that is predominately employed in the video, said specified presentation style being a one of the presentation styles in a set of possible presentation styles; using the training dataset to independently learn a different classifier for each possible unordered pair of presentation styles in the set of possible presentation styles; and combining the different classifiers using probabilistic fusion, said combination producing the video presentation style classifier. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
Specification