US 12,267,557 B2
Video content recommendation method and apparatus, and computer device
Junhao Wu, Shanghai (CN); and Peng Xie, Shanghai (CN)
Assigned to SHANGHAI BILIBILI TECHNOLOGY CO., LTD., Shanghai (CN)
Appl. No. 18/014,339
Filed by SHANGHAI BILIBILI TECHNOLOGY CO., LTD., Shanghai (CN)
PCT Filed Jun. 22, 2021, PCT No. PCT/CN2021/101626
§ 371(c)(1), (2) Date Jan. 3, 2023,
PCT Pub. No. WO2022/007626, PCT Pub. Date Jan. 13, 2022.
Claims priority of application No. 202010645506.3 (CN), filed on Jul. 6, 2020.
Prior Publication US 2023/0300417 A1, Sep. 21, 2023
Int. Cl. H04N 21/466 (2011.01); H04N 21/45 (2011.01)
CPC H04N 21/4668 (2013.01) [H04N 21/4532 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A computer-implemented method of performing online video recommendation, comprising:
retrieving, by a computing device, a set of to-be-selected videos from a video library stored on a video server, the set of to-be-selected videos comprising videos based on video playback interest information determined for a first user and videos predetermined as popular based on viewing activities of a plurality of users;
consecutively selecting by the computing device a first video from the set of to-be-selected videos and temporarily pre-adding the first video to a last position of a sequence of recommendation videos;
capturing, by the computing device, from the sequence of recommendation videos, a sub-sequence comprising a preset quantity of videos, wherein the sub-sequence comprises the first video;
obtaining, by the computing device, a target attribute and an initial recommendation score of the first video;
identifying, by the computing device, at least one target video in the sub-sequence, wherein the at least one target video has the target attribute and is different from the first video, and determining a quantity n of the at least one target video;
modifying, by the computing device, the initial recommendation score of the first video based on the quantity n and a position distance between each of the at least one target video and the first video to obtain a modified recommendation score, wherein the modifying the initial recommendation score of the first video based on the quantity n and a position distance between each of the at least one target video and the first video to obtain a modified recommendation score further comprises:
obtaining a position sequence number i of the at least one target video in the sub-sequence and a position sequence number k of the first video in the sub-sequence in response to determining that the quantity n is less than a preset threshold N, and
modifying the initial recommendation score based on the position sequence number i of the at least one target video, the position sequence number k of the first video, and a preset modification formula, wherein the preset modification formula comprises:

OG Complex Work Unit Math
wherein scorek represents the initial recommendation score of the first video, score′k represents the modified recommendation score of the first video, count(tagsk) represents a quantity of tag attributes associated with the first video, count(tagsi) represents a quantity of tag attributes associated with the target video, demote(distance(i, k), tag) represents a first modification function associated with tag attributes, demote(distance(i, k), up) represents a second modification function associated with uploader attributes indicating information about users who uploads videos:
obtaining, by the computing device, modified recommendation scores of all videos in the set of to-be-selected videos; and
selecting, by the computing device, a video with a highest modified recommendation score from the set of to-be-selected videos and adding the video with the highest modified recommendation score to the last position of the sequence of recommendation videos.