Open-domain trending hashtag recommendations

    公开(公告)号:US12050647B2

    公开(公告)日:2024-07-30

    申请号:US17877469

    申请日:2022-07-29

    Applicant: Adobe Inc.

    CPC classification number: G06F16/9024 G06N3/045 G06Q50/01

    Abstract: Techniques for recommending hashtags, including trending hashtags, are disclosed. An example method includes accessing a graph. The graph includes video nodes representing videos, historical hashtag nodes representing historical hashtags, and edges indicating associations among the video nodes and the historical hashtag nodes. A trending hashtag is identified. An edge is added to the graph between a historical hashtag node representing a historical hashtag and a trending hashtag node representing the trending hashtag, based on a semantic similarity between the historical hashtag and the trending hashtag. A new video node representing a new video is added to the video nodes of the graph. A graph neural network (GNN) is applied to the graph, and the GNN predicts a new edge between the trending hashtag node and the new video node. The trending hashtag is recommended for the new video based on prediction of the new edge.

    OPEN-DOMAIN TRENDING HASHTAG RECOMMENDATIONS

    公开(公告)号:US20240037149A1

    公开(公告)日:2024-02-01

    申请号:US17877469

    申请日:2022-07-29

    Applicant: Adobe Inc.

    CPC classification number: G06F16/9024 G06N3/0454 G06Q50/01

    Abstract: Techniques for recommending hashtags, including trending hashtags, are disclosed. An example method includes accessing a graph. The graph includes video nodes representing videos, historical hashtag nodes representing historical hashtags, and edges indicating associations among the video nodes and the historical hashtag nodes. A trending hashtag is identified. An edge is added to the graph between a historical hashtag node representing a historical hashtag and a trending hashtag node representing the trending hashtag, based on a semantic similarity between the historical hashtag and the trending hashtag. A new video node representing a new video is added to the video nodes of the graph. A graph neural network (GNN) is applied to the graph, and the GNN predicts a new edge between the trending hashtag node and the new video node. The trending hashtag is recommended for the new video based on prediction of the new edge.

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