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    PROBABILISTIC SEARCH BIASING AND RECOMMENDATIONS
    1.
    发明申请
    PROBABILISTIC SEARCH BIASING AND RECOMMENDATIONS 有权

    公开(公告)号：US20220270121A1

    公开(公告)日：2022-08-25

    申请号：US17654484

    申请日：2022-03-11

    申请人： Mercari Inc.

    发明人： Byong Mok OH ,  Dhruv MEHROTRA ,  Chiaki OSAKA ,  Naoya MAKINO ,  Patrick Michael WISEMAN ,  Minami SUEYASU

    IPC分类号： G06Q30/02 ,  G06Q30/06 ,  G06F16/903 ,  G06F16/908 ,  G06F16/9032 ,  G06N3/08 ,  G06F16/951

    摘要： Disclosed herein are system, method, and computer program product embodiments for probabilistic search biasing and recommendations. A system including at least one processor may be configured to receive an input relating to an identified item, generate a database query based on the input, and receive a response to the database query. The response may include information on comparable items similar to the identified item, and corresponding metadata for the comparable items. The corresponding metadata may include a range of values corresponding to the comparable items. The system may be further configured to generate a probability score for at least two values of the range of values, based at least on the corresponding metadata for the comparable items. The system may be further configured to output at least a suggested value based on at least the generated probability score for the range of values and prompt for further input.

    ITEM NAME SUGGEST
    2.
    发明申请
    ITEM NAME SUGGEST 有权

    公开(公告)号：US20210357382A1

    公开(公告)日：2021-11-18

    申请号：US17302580

    申请日：2021-05-06

    申请人： Mercari, Inc.

    发明人： Sahil RISHI ,  Manikandan SANKAR ,  Byong Mok OH ,  Yodhavee CHUENBUNLUESOOK ,  Ankit Kumar BARUAH ,  Shuichi IIDA

    IPC分类号： G06F16/23 ,  G06F7/02

    摘要： Described herein are embodiments for assisting in creating a listing for a For Sale Object (FSO). An item name suggestion module receives seller input and provides suggested entries for the listing to help the seller describe the FSO more accurately and consistently. A hierarchical database provides a structure for ordering suggested entries, with the structure ordered based on scores. The scores are based on rules that relate item characteristics and take into account rankings of those item characteristics with respect to one another. Metadata tags that are used by the online merchandise platforms can be identified and included in the listing, even if a seller is not familiar with the metadata tags. The hierarchical database also connects or associates item characteristics in groups that describe specific FSO. The connections can help to optimize search results as the listing is completed by the seller.

    MACHINE GENERATED ONTOLOGY
    3.
    发明申请
    MACHINE GENERATED ONTOLOGY 有权

    公开(公告)号：US20220253473A1

    公开(公告)日：2022-08-11

    申请号：US17168972

    申请日：2021-02-05

    申请人： Mercari, Inc.

    发明人： Mohammad-Mahdi MOAZZAMI ,  Manikandan SANKAR ,  Byong Mok OH ,  Sahil RISHI ,  Sho ARORA

    IPC分类号： G06F16/36 ,  G06F16/35 ,  G06Q10/08 ,  G06N3/08

    摘要： Described herein are embodiments for machine-generating and naming ontologies for for-sale items. A neural network may be used to train information describing for-sale items into feature vectors that describe the for-sale items. These feature vectors may be sorted into clusters based on their relative proximity using clustering algorithms. The resulting clusters may be sub-divided into smaller clusters depending on the precision used in the clustering algorithm. The set of clusters may form a hierarchical data structure where each level has clusters determined at a certain precision and each lower level sub-divides those clusters. The clusters may be named based on the most salient facets that describe the for-sale items in the clusters.

    ITEM MATCHING AND PRICING BASED ON HISTORICAL PRICING DATA AND CLASSIFICATION OF PARTIES TO RELATED TRANSACTIONS
    5.
    发明公开
    ITEM MATCHING AND PRICING BASED ON HISTORICAL PRICING DATA AND CLASSIFICATION OF PARTIES TO RELATED TRANSACTIONS 审中-公开

    公开(公告)号：US20240104626A1

    公开(公告)日：2024-03-28

    申请号：US17936176

    申请日：2022-09-28

    申请人： Mercari, Inc.

    发明人： Byong Mok OH ,  Hayato RYUKI ,  Ajay DAPTARDER ,  Thea LEE ,  Colin SMITH

    IPC分类号： G06Q30/06

    CPC分类号： G06Q30/0631

    摘要： Embodiments described herein include modeling of seller profiles and behaviors on an e-commerce site to induce more listings and sales within the e-commerce site. For every seller and potential seller on the e-commerce site, their behaviors is to be understood and modeled in order to draw out more listings and completed sales per seller. An example embodiment of the present disclosure includes receiving a first information listing. At least one classification of the information listing may be generated performing at least one machine-learning (ML) process based at least in part on at least one ML model and the first information listing. A recommendation based on the classification of the first information listing may be generated. The recommendation may be recommending. A second information listing may be created.

    COMPUTER TECHNOLOGY FOR AUTOMATED PRICING GUIDANCE
    7.
    发明申请
    COMPUTER TECHNOLOGY FOR AUTOMATED PRICING GUIDANCE 有权

    公开(公告)号：US20210406937A1

    公开(公告)日：2021-12-30

    申请号：US16912401

    申请日：2020-06-25

    申请人： Mercari, Inc.

    发明人： Byong Mok OH ,  Takuma YAMAGUCHI ,  Rishabh Kumar SHRIVASTAVA ,  Fritz Mikio KURIBAYASHI ,  John Alexander LAGERLING ,  Minami TANAKA

    IPC分类号： G06Q30/02 ,  G06Q30/06 ,  G06N3/04 ,  G06N3/08

    摘要： Disclosed herein are embodiments for automated intelligent price guidance of listings for a for sale object (FSO) being offered by a seller. Some embodiments may operate by: receiving information relating to the FSO, including specifications for selling the FSO, wherein the specifications include an original offer price and a time window for selling the FSO; determining a category of the FSO; generating an optimal offer price for the FSO based on one or more of: (a) past listings of previously sold FSOs that have a same or similar category of the FSO; (b) the specifications, including the time window; (c) a category decay curve applicable to the category; and (d) seller flexibility curve of the seller; and through the use of a machine learning neural networking analysis suggesting the optimal offer price to the seller as an offer price for a listing corresponding to the FSO, wherein this price is evaluated over time and suggestions are made accordingly.