Clustering interactions for user missions

    公开(公告)号:US10311499B1

    公开(公告)日:2019-06-04

    申请号:US14666134

    申请日:2015-03-23

    Abstract: Techniques for identifying clusters of user interactions and shopping missions may be provided. For example, the system may receive a history of interactions between a user and one or more network pages. The system may identify a most recent event from the history of interactions and identify a cluster that includes other events from the history of interactions that are of a same category as the most recent event. The determination of the cluster may be based in part on item attributes associated with the item presented on the at least one of the one or more network pages. The most recent event may then be associated with the cluster. In some examples, a shopping mission is determined and one or more notifications are provided to a user, merchant, or electronic marketplace in association with the identified shopping mission.

    Clustering interactions for user missions

    公开(公告)号:US11049167B1

    公开(公告)日:2021-06-29

    申请号:US16390624

    申请日:2019-04-22

    Abstract: Techniques for identifying clusters of user interactions and shopping missions may be provided. For example, the system may receive a history of interactions between a user and one or more network pages. The system may identify a most recent event from the history of interactions and identify a cluster that includes other events from the history of interactions that are of a same category as the most recent event. The determination of the cluster may be based in part on item attributes associated with the item presented on the at least one of the one or more network pages. The most recent event may then be associated with the cluster. In some examples, a shopping mission is determined and one or more notifications are provided to a user, merchant, or electronic marketplace in association with the identified shopping mission.

    Artificial intelligence system for generating intent-aware recommendations

    公开(公告)号:US10706450B1

    公开(公告)日:2020-07-07

    申请号:US15896775

    申请日:2018-02-14

    Abstract: The present disclosure is directed to training and using machine learning models to determine user intent from a search query, for example via a semantic parse that identifies particular catalog fields for items in an electronic catalog that would satisfy the user's current mission as reflected in their search query intent. The determined intent can then be used to filter recommendations and/or pre-select attribute-value input fields on detail pages displayed after the user navigates away from the search results page, until the mission is complete.

    Product recommendations
    6.
    发明授权

    公开(公告)号:US09904949B1

    公开(公告)日:2018-02-27

    申请号:US13924085

    申请日:2013-06-21

    CPC classification number: G06Q30/0631

    Abstract: The technology may monitor context items as a content page is navigated. A similarities dataset may be selected from a plurality of similarities datasets as a source of recommendations based on the context items. Recommendations in the similarities dataset selected may be ranked based on the context items. The recommendations may be provided based on the ranking.

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