User-preferred item attributes
    3.
    发明授权

    公开(公告)号:US11580585B1

    公开(公告)日:2023-02-14

    申请号:US16915201

    申请日:2020-06-29

    Abstract: Disclosed are one or more embodiments for a unique and personalized experience for a user interacting with an electronic commerce site by identifying user-preferred item attributes using supervised machine learning and presenting items to the user in an arrangement that is based on the identified item attributes. A shopping mission is determined according to user interactions with an electronic commerce site. The shopping mission is applied to an attribute prediction model that is trained to detect user-preferred item attributes for items included the item category and estimate a likelihood that an item containing a particular attribute will be purchased or interacted with during the interactions with the electronic commerce site.

    Automated identification of item attributes relevant to a browsing session

    公开(公告)号:US11282124B1

    公开(公告)日:2022-03-22

    申请号:US16403029

    申请日:2019-05-03

    Abstract: Systems and methods are provided for electronic catalog user experience improvements based on extracted item attributes. An example method includes obtaining information identifying items viewed during a user browsing session, the items being included in an electronic catalog, and the electronic catalog being organized according to a hierarchy, with the hierarchy comprising a plurality of categories. Information identifying attributes associated with the identified items is identified, and the attributes are ranked according to attribute relevance score. Items are determined for recommendation to the user based on the ranked attribute relevance scores, with the determined items being selected from items included in the electronic catalog which are also associated with a same category as the identified items.

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