Recommendation system to enhance video content recommendation
First Claim
1. An online system for generating content recommendations for a target user of the system, comprising:
- a processor; and
a non-transitory computer readable medium configured to store instructions that, when executed by the processor, cause the processor to perform steps comprising;
maintaining, by the online system, a collection of publicly available videos;
generating a plurality of sets of video candidates selected from the collection of publicly available videos by;
accessing a plurality of recommendation functions that each apply different types of selection criteria to uniquely select and rank the video candidates for the set that corresponds to that recommendation function, the video candidates each having a ranking score for ranking relative to other video candidates in the set; and
receiving, from each recommendation function, the set of video candidates selected and ranked by the recommendation function, each set of video candidates representing video content that is likely to be of interest to the target user, the sets of video candidates selected from the collection of publicly available videos to supplement a display for the target user of other video content posted by the target user'"'"'s connections in the online system;
filtering the video candidates from the sets from each of the recommendation functions to remove one or more video candidates that violate a video content policy of the online system;
performing a second ranking of the filtered video candidates as a combined group from the sets by;
extracting features from the filtered video candidates;
assigning weights to the features associated with the filtered video candidates, a weight of a feature generated by a ranking model trained on the features of the video candidates, and indicating a relative importance of the feature to the target user;
generating ranking scores for the filtered video candidates based on the weights of the features associated with the filtered video candidates; and
selecting a plurality of videos from the filtered video candidates as recommendations to the target user based on the ranking scores associated with the video candidates; and
providing for display to the target user the selected videos along with other video content posted by the target user'"'"'s connections in the online system.
2 Assignments
0 Petitions
Accused Products
Abstract
An online system provides video recommendations to a target user of the online system as a supplement to videos provided to the target user that were posted by the user'"'"'s connections in the online system. The recommended videos are selected from publicly available video content and are likely to be of interest to the target user. The online system has video candidate generators that select video candidates based on a variety of selection criteria. The selected video candidates are filtered to identify inappropriate content or videos that the target user has already viewed for elimination from candidacy. The filtered video candidates are ranked based on weights of features of the video candidates. Based on the ranking, the online system selects videos above a threshold as recommendations to the target user.
5 Citations
22 Claims
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1. An online system for generating content recommendations for a target user of the system, comprising:
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a processor; and a non-transitory computer readable medium configured to store instructions that, when executed by the processor, cause the processor to perform steps comprising; maintaining, by the online system, a collection of publicly available videos; generating a plurality of sets of video candidates selected from the collection of publicly available videos by; accessing a plurality of recommendation functions that each apply different types of selection criteria to uniquely select and rank the video candidates for the set that corresponds to that recommendation function, the video candidates each having a ranking score for ranking relative to other video candidates in the set; and receiving, from each recommendation function, the set of video candidates selected and ranked by the recommendation function, each set of video candidates representing video content that is likely to be of interest to the target user, the sets of video candidates selected from the collection of publicly available videos to supplement a display for the target user of other video content posted by the target user'"'"'s connections in the online system; filtering the video candidates from the sets from each of the recommendation functions to remove one or more video candidates that violate a video content policy of the online system; performing a second ranking of the filtered video candidates as a combined group from the sets by; extracting features from the filtered video candidates; assigning weights to the features associated with the filtered video candidates, a weight of a feature generated by a ranking model trained on the features of the video candidates, and indicating a relative importance of the feature to the target user; generating ranking scores for the filtered video candidates based on the weights of the features associated with the filtered video candidates; and selecting a plurality of videos from the filtered video candidates as recommendations to the target user based on the ranking scores associated with the video candidates; and providing for display to the target user the selected videos along with other video content posted by the target user'"'"'s connections in the online system. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A non-transitory computer readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to perform the steps including:
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maintaining, by an online system, a collection of publicly available videos; generating a plurality of sets of video candidates selected from the collection of publicly available videos by; accessing a plurality of recommendation functions that each apply different types of selection criteria to uniquely select and rank the video candidates for the set that corresponds to that recommendation function, the video candidates each having a ranking score for ranking relative to other video candidates in the set; and receiving, from each recommendation function, the set of video candidates selected and ranked by the recommendation function, each set of video candidates representing video content that is likely to be of interest to the target user, the sets of video candidates selected from the collection of publicly available videos to supplement a display for the target user of other video content posted by the target user'"'"'s connections in the online system; filtering the video candidates from the sets from each of the recommendation functions to remove one or more video candidates that violate a video content policy of the online system to generate a plurality of filtered video candidates; performing a second ranking of the filtered video candidates as a combined group from the sets by; extracting features from the filtered video candidates; assigning weights to the features associated with the filtered video candidates, a weight of a feature generated by a ranking model trained on the features of the video candidates, and indicating a relative importance of the feature to the target user; generating ranking scores for the filtered video candidates based on the weights of the features associated with the filtered video candidates; and selecting a plurality of videos from the filtered video candidates as recommendations to the target user based on the ranking scores associated with the video candidates; and providing for display to the target user the selected videos along with other video content posted by the target user'"'"'s connections in the online system. - View Dependent Claims (11, 12, 13, 14, 15, 16)
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17. A method for generating content recommendations for a target user of an online system, comprising:
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maintaining, by the online system, a collection of publicly available videos; generating a plurality of sets of video candidates selected from the collection of publicly available videos by; accessing a plurality of recommendation functions that each apply different types of selection criteria to uniquely select and rank the video candidates for the set that corresponds to that recommendation function, the video candidates each having a ranking score for ranking relative to other video candidates in the set; and receiving, from each recommendation function, the set of video candidates selected and ranked by the recommendation function, each set of video candidates representing video content that is likely to be of interest to the target user, the sets of video candidates selected from the collection of publicly available videos to supplement a display for the target user of other video content posted by the target user'"'"'s connections in the online system; filtering the video candidates from the sets from each of the recommendation functions to remove one or more video candidates that violate a video content policy of the online system; performing a second ranking of the filtered video candidates as a combined group from the sets by; extracting features from the filtered video candidates; assigning weights to the features associated with the filtered video candidates, a weight of a feature generated by a ranking model trained on the features of the video candidates, and indicating a relative importance of the feature to the target user; generating ranking scores for the filtered video candidates based on the weights of the features associated with the filtered video candidates; selecting a plurality of videos from the filtered video candidates as recommendations to the target user based on the ranking scores associated with the video candidates; and providing for display to the target user the selected videos along with other video content posted by the target user'"'"'s connections in the online system. - View Dependent Claims (18, 19, 20, 21, 22)
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Specification