VIDEO RECOMMENDER SYSTEM BY KNOWLEDGE BASED MULTI-MODAL GRAPH NEURAL NETWORKS

    公开(公告)号:US20230237093A1

    公开(公告)日:2023-07-27

    申请号:US17649091

    申请日:2022-01-27

    申请人: ADOBE INC.

    IPC分类号: G06F16/735 G06N3/08

    CPC分类号: G06F16/735 G06N3/08

    摘要: Systems and methods for item recommendation are described. Embodiments of the present disclosure receive input indicating a relationship between a user and a first content item; generate a knowledge graph based on the input, wherein the knowledge graph comprises relationship information between the user and a plurality of content items; generate a first feature embedding representing the user and a second feature embedding representing a second content item of the plurality of content items based on the knowledge graph, wherein the second feature embedding is generated using a first modality for a query vector of an attention mechanism and a second modality for a key vector and a value vector of the attention mechanism; compare the first feature embedding to the second feature embedding to obtain a similarity score; and recommend the second content item for the user based on the similarity score.

    METHODS, SYSTEMS, AND MEDIA FOR MODIFYING SEARCH RESULTS BASED ON SEARCH QUERY RISK

    公开(公告)号:US20230229698A1

    公开(公告)日:2023-07-20

    申请号:US18123542

    申请日:2023-03-20

    申请人: Google LLC

    摘要: Methods, systems, and media for demoting search results based on search query risk are provided. In some embodiments, a method for demoting search results includes: receiving a search query for a video content item; generating a plurality of search results in response to the search query; calculating a set of result goodness values; calculating a query goodness value associated with the search query based on the set of result goodness values; identifying a threshold goodness value based on the query goodness value; in response to determining that a first result goodness value of the set of result goodness values is less than the threshold goodness value, demoting a first search result of the plurality of search results, wherein the first result goodness value is associated with the first search result; and causing at least a portion of the plurality of search results to be presented based on the demotion.