DETERMINING RECOMMENDED SEARCH TERMS FOR A USER OF AN ONLINE CONCIERGE SYSTEM

    公开(公告)号:US20230139335A1

    公开(公告)日:2023-05-04

    申请号:US18090506

    申请日:2022-12-29

    Abstract: An online concierge system may determine recommended search terms for a user. The online concierge system may receive a request from a user to view a user interface configured to receive a search query. The online concierge system retrieves long-term activity data including previous search terms entered by the user while searching for items to add to an online shopping cart. For each previous search term, the online concierge system retrieves categorical search terms corresponding to one or more categories to which the previous search term was mapped. The online concierge system determines a set of nearby categorical search terms and sends, for display via a client device, the set of nearby categorical search terms as recommended search terms.

    SELECTING AN ITEM FOR INCLUSION IN AN ORDER FROM A USER OF AN ONLINE CONCIERGE SYSTEM FROM A GENERIC ITEM DESCRIPTION RECEIVED FROM THE USER

    公开(公告)号:US20220358560A1

    公开(公告)日:2022-11-10

    申请号:US17308993

    申请日:2021-05-05

    Abstract: An online concierge system maintains a taxonomy associating one or more specific items offered by a warehouse with a generic item description. When the online concierge system receives a generic item description from a user for inclusion in an order, the online concierge system uses the taxonomy to select a set of items associated with the generic item description. Based on probabilities of the user purchasing various items of the set, the online concierge system selects an item of the set for inclusion in the order For example, the online concierge system selects an item of the set for which the user has a maximum probability of being purchased. Subsequently, the online concierge system displays an interface for the user that is prepopulated with information identifying the selected item of the set.

    USER INTERFACE THAT PRE-POPULATES ITEMS IN AN ORDER MODULE FOR A USER OF AN ONLINE CONCIERGE SYSTEM USING A PREDICTION MODEL

    公开(公告)号:US20220335493A1

    公开(公告)日:2022-10-20

    申请号:US17232651

    申请日:2021-04-16

    Abstract: An online concierge system maintains historical orders received from a user that include one or more items. For items included in one more historical orders, the online concierge system determines an interval between orders including an item, providing an indication of a frequency with which the user orders the item. When the online concierge system receives a request to create an order from the user, in response to an amount of time between a most recently received order including the item and a time when the request was received is within a threshold duration of the interval between orders including the item, the online concierge system selects an item from a category including the item. The selected item may be the item or an alternative item in the category. Subsequently, the online concierge system displays an interface for the user that is prepopulated with information identifying the selected item.

    DETERMINING RECOMMENDED SEARCH TERMS FOR A USER OF AN ONLINE CONCIERGE SYSTEM

    公开(公告)号:US20210287271A1

    公开(公告)日:2021-09-16

    申请号:US16815846

    申请日:2020-03-11

    Abstract: An online concierge system may determine recommended search terms for a user. The online concierge system may receive a request from a user to view a user interface configured to receive a search query. The online concierge system retrieves long-term activity data including previous search terms entered by the user while searching for items to add to an online shopping cart. For each previous search term, the online concierge system retrieves categorical search terms corresponding to one or more categories to which the previous search term was mapped. The online concierge system determines a set of nearby categorical search terms and sends, for display via a client device, the set of nearby categorical search terms as recommended search terms.

    POPULATING CATALOG DATA WITH ITEM PROPERTIES BASED ON SEGMENTATION AND CLASSIFICATION MODELS

    公开(公告)号:US20200034782A1

    公开(公告)日:2020-01-30

    申请号:US16048800

    申请日:2018-07-30

    Abstract: A method for populating an inventory catalog includes receiving an image showing an item in the inventory catalog and comprising a plurality of pixels. A machine learned segmentation neural network is retrieved to determine location of pixels in an image that are associated with an image label and the property. The method determines a subset of pixels associated with the item label in the received image and identifies locations of the subset of pixels of the received image, and extracts the subset of pixels from the received image. The method retrieves a machine learned classifier to determine whether an image shows the item label. The method determines, using the machine learned classifier, that the extracted subset of pixels shows the item label. The method updates the inventory catalog for the item to indicate that the item has the property associated with the item label.

    PREDICTIVE INVENTORY AVAILABILITY
    170.
    发明申请

    公开(公告)号:US20190236740A1

    公开(公告)日:2019-08-01

    申请号:US15885492

    申请日:2018-01-31

    Abstract: A method for predicting inventory availability, involving receiving a delivery order including a plurality of items and a delivery location, and identifying a warehouse for picking the plurality of items. The method retrieves a machine-learned model that predicts a probability that an item is available at the warehouse. The machine-learned model is trained, using machine learning, based in part on a plurality of datasets. The plurality of datasets include data describing items included in previous delivery orders, whether each item in each previous delivery order was picked, a warehouse associated with each previous delivery order, and a plurality of characteristics associated with each of the items. The method predicts the probability that one of the plurality of items in the delivery order is available at the warehouse, and generates an instruction to a picker based on the probability. An instruction is transmitted to a mobile device of the picker.

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