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    SYSTEM AND METHOD FOR POST TRANSACTION SEASONAL ITEM RECOMMENDATIONS
    1.
    发明公开
    SYSTEM AND METHOD FOR POST TRANSACTION SEASONAL ITEM RECOMMENDATIONS 审中-公开

    公开(公告)号：US20240232941A1

    公开(公告)日：2024-07-11

    申请号：US18092062

    申请日：2022-12-30

    Applicant: Walmart Apollo, LLC

    Inventor： Parth Ramesh Vajge ,  Luyi Ma ,  Hyun Duk Cho ,  Sushant Kumar ,  Kannan Achan ,  Lawrence David Lin

    IPC: G06Q30/0251 ,  G06Q30/0241

    CPC classification number: G06Q30/0252 ,  G06Q30/0256 ,  G06Q30/0277

    Abstract: Systems and methods for post transaction seasonal item recommendations are disclosed. In some embodiments, a current seasonal time window associated with a seasonal event and some seasonal product types is determined. Based on historical transaction data of the seasonal product types, a first seasonal index score is computed for each item, and a second seasonal index score is computed for each product type including one or more items. A seasonal rank score is generated for each item based on the first seasonal index score and the second seasonal index score, such that the items in the historical transaction data are ranked based on their respective seasonal rank scores. Based on the ranked items and a transaction order from a user, a list of recommended items is generated and displayed to the user.

    METHODS AND SYSTEMS FOR DETERMINING HOUSEHOLD CHARACTERISTICS
    4.
    发明公开
    METHODS AND SYSTEMS FOR DETERMINING HOUSEHOLD CHARACTERISTICS 审中-公开

    公开(公告)号：US20230245202A1

    公开(公告)日：2023-08-03

    申请号：US17589003

    申请日：2022-01-31

    Applicant: Walmart Apollo, LLC

    Inventor： Nimesh Sinha ,  Sneha Gupta ,  Rishi Rajasekaran ,  Yue Xu ,  Yokila Arora ,  Hyun Duk Cho ,  Sushant Kumar ,  Kannan Achan

    IPC: G06Q30/06 ,  G06Q30/02

    CPC classification number: G06Q30/0631 ,  G06Q30/0271 ,  G06Q30/0204

    Abstract: A system and method for recommending products based on characteristics of a customer's household. The system and method associates age dependent products with developmental stages on a universal developmental scale and determines a subset of age dependent products based on prior engagements by the customer's household. Using the development stages associated with the subset of age dependent products characteristics of the customer's household may determine specifically the number and ages of juveniles in the customer's household. Performing Gaussian mixture model or multivariate kernel density estimation on the developmental stages associated with the engagements of customer's household, the age(s) and number of juveniles respectively may be determined and recommendations of products and services to the customer or customer's household based upon these characteristics may be advantageously made.

    Identifying value conscious users
    5.
    发明授权
    Identifying value conscious users 有权

    公开(公告)号：US11676168B2

    公开(公告)日：2023-06-13

    申请号：US16260472

    申请日：2019-01-29

    Applicant: Walmart Apollo, LLC

    Inventor： Sushant Kumar ,  Hyun Duk Cho ,  Kannan Achan ,  Venkata Syam Prakash Rapaka

    IPC: G06Q30/02 ,  G06Q30/0207 ,  G06Q30/0204 ,  G06Q30/0601 ,  G06Q30/06

    CPC classification number: G06Q30/0224 ,  G06Q30/0204 ,  G06Q30/0631

    Abstract: A method can include retrieving product information from a website database to identify a first product as a value-sensitive product identified with at least a value price tag. The method can include determining second users who are not value conscious about the first product. The method can also include preparing first and second recommendations and promotions for the first product, wherein the first recommendation comprises one or more value-sensitive products. The method additionally can include transmitting machine readable instructions to display the first recommendations and promotions for the first product for viewing by the first user. The method also can include transmitting machine readable instructions to display the second recommendations and promotions for the first product for viewing by the second user. Other embodiments are disclosed herein.

    SYSTEM AND METHOD FOR DIVERSIFYING COMPLEMENTARY ITEM RECOMMENDATIONS BASED ON USER PREFERENCES
    7.
    发明申请
    SYSTEM AND METHOD FOR DIVERSIFYING COMPLEMENTARY ITEM RECOMMENDATIONS BASED ON USER PREFERENCES 有权

    公开(公告)号：US20220245705A1

    公开(公告)日：2022-08-04

    申请号：US17163380

    申请日：2021-01-30

    Applicant: Walmart Apollo, LLC

    Inventor： Luyi Ma ,  Nimesh Sinha ,  Hyun Duk Cho ,  Sushant Kumar ,  Kannan Achan

    IPC: G06Q30/06 ,  G06N5/04 ,  G06N20/00

    Abstract: A method including determining, in real-time, a diversity preference score for a user based at least in part on an anchor item chosen by the user via a user interface executed on a user device of the user. The method also can include determining, in real-time, a comparison result between the diversity preference score and a diversity preference threshold. The method further can include generating, in real-time, a personalized recommendation pool based on (a) the comparison result, (b) a complementary recommendation pool generated based at least in part on the anchor item, and (c) a diversity objective function. In many embodiments, when the comparison result indicates that the diversity preference score is greater than the diversity preference threshold, the diversity objective function can be associated with cross-domain diversity. In a number of embodiments, when the comparison result indicates that the diversity preference score is not greater than the diversity preference threshold, the diversity objective function can be associated with within-domain diversity. The method additionally can include transmitting, in real-time through the computer network, the personalized recommendation pool to be displayed with the anchor item on the user interface. Other embodiments are disclosed.

    SYSTEMS AND METHODS FOR PERSONALIZING SEARCH ENGINE RECALL AND RANKING USING MACHINE LEARNING TECHNIQUES
    8.
    发明申请
    SYSTEMS AND METHODS FOR PERSONALIZING SEARCH ENGINE RECALL AND RANKING USING MACHINE LEARNING TECHNIQUES 有权

    公开(公告)号：US20220245698A1

    公开(公告)日：2022-08-04

    申请号：US17163405

    申请日：2021-01-30

    Applicant: Walmart Apollo, LLC

    Inventor： Hyun Duk Cho ,  Sushant Kumar ,  Kannan Achan ,  Nimesh Sinha ,  Aysenur Inan

    IPC: G06Q30/06 ,  G06N20/00 ,  G06N5/04 ,  G06F16/2457

    Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of: generating one or more attribute affinity scores for one or more attributes associated with an item type category, wherein the one or more attribute affinity scores predict a user's affinity for attribute values associated with the one or more attributes; generating a respective attribute importance score for each of the one or more attributes, the respective attribute importance score predicting a respective importance of each of the one or more attributes to the user; and generating personalized search results that are ordered based, at least in part, on the one or more attribute affinity scores and the respective attribute importance scores. Other embodiments are disclosed herein.

    SYSTEMS AND METHODS FOR WEBPAGE PERSONALIZATION
    10.
    发明申请
    SYSTEMS AND METHODS FOR WEBPAGE PERSONALIZATION 有权

    公开(公告)号：US20220141307A1

    公开(公告)日：2022-05-05

    申请号：US17578323

    申请日：2022-01-18

    Applicant: Walmart Apollo, LLC

    Inventor： Venkata Syam Prakash Rapaka ,  Kannan Achan ,  Kaushiki Nag ,  Sushant Kumar

    IPC: H04L67/306 ,  G06Q30/02 ,  G06F16/2452 ,  G06F16/2457

    Abstract: A system can include one or more processing modules and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processing modules and perform receiving, from an electronic device, a search query from a user of a plurality of users; processing first data; and facilitating displaying a set of items. Processing the first data can comprise determining one or more keywords by capturing the one or more keywords during a time window; creating a feature set of second data associated with at least a portion of the plurality of users; determining a set of items of the item set as being based at least in part on an item vector representation and a keyword vector representation; determining a respective purchase probability associated with each item of the set of items of the item set; ranking the set of items.

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