APPLYING A QUANTITATIVE RANGE FOR QUALITATIVE TERMS

    公开(公告)号:US20180107917A1

    公开(公告)日:2018-04-19

    申请号:US15297902

    申请日:2016-10-19

    Applicant: eBay Inc.

    Abstract: In various example embodiments, a system and method for applying a quantitative range for qualitative terms. In one example, a method includes gathering user interactions, identifying a qualitative term included in the user interactions, building an electronic knowledge graph that associates the qualitative term with a quantitative range for the product identified using the qualitative term according to values in the user interactions that include the qualitative term, receiving a query for the product that includes the qualitative term, and performing, in response to receiving the query, a search that limits results according to the quantitative range stored in the knowledge graph.

    Methods and systems for query segmentation

    公开(公告)号:US11640436B2

    公开(公告)日:2023-05-02

    申请号:US15681663

    申请日:2017-08-21

    Applicant: eBay Inc.

    Abstract: A query segmentation system segments a search query into a query segment that identifies search results from items stored on a database. The query segmentation system receives a query string, and the query string comprises a plurality of tokens. A first token and a second token are identified from the plurality of tokens, and a first vector and a second vector associated with the first token and the second token respectively are determined. The query segmentation system determines whether to include the first and second tokens in a single query segment based on the first and second vectors. The single query segment is processed to identify the search results from the database.

    DETECTION OF MISSION CHANGE IN CONVERSATION

    公开(公告)号:US20220020375A1

    公开(公告)日:2022-01-20

    申请号:US17490788

    申请日:2021-09-30

    Applicant: eBay Inc.

    Abstract: Methods, systems, and computer programs are presented for detecting a mission changes in a conversation. A user utterance from a user device is received. The user utterance is part of a conversation with an intelligent assistant. The conversation includes preceding user utterances in pursuit of a first mission. It is determined that the user utterance indicates a mission change from the first mission to a second mission based on an application of a machine-learned model to the user utterance and the preceding user utterances. The machine-learned model has been trained repeatedly with past utterances of other users over a time period, the determining based on a certainty of the indication satisfying a certainty threshold. Responsive to the determining that the user utterance indicates the mission change from the first mission to a second mission, a reply to the user utterance is generated to further the second mission rather than the first mission.

    PROCESSING TRANSACTIONAL FEEDBACK
    18.
    发明申请

    公开(公告)号:US20210064824A1

    公开(公告)日:2021-03-04

    申请号:US16461125

    申请日:2018-05-18

    Applicant: eBay Inc.

    Abstract: Disclosed are systems and methods for receiving a plurality of comments at a particular phase of a transaction with a member of a networked system, classifying one or more of the plurality of comments into one of a set of predetermined sentiment classifications, applying a trained machine learning system to select a category from a set of predefined categories for each of the one or more comments, applying a natural language processing module to generate a sub-category for each of the one or more comments, associating the generated sub-categories with their respective categories for the one or more comments, and generating a display of the determined categories for the particular transaction with the generated sub-categories, each generated sub-category being graphically connected to their respective categories.

    PROCESSING TRANSACTIONAL FEEDBACK
    20.
    发明公开

    公开(公告)号:US20240078388A1

    公开(公告)日:2024-03-07

    申请号:US18388239

    申请日:2023-11-09

    Applicant: eBay Inc.

    CPC classification number: G06F40/30 G06N20/00 H04L51/212

    Abstract: Disclosed are systems and methods for receiving a plurality of comments at a particular phase of a transaction with a member of a networked system, classifying one or more of the plurality of comments into one of a set of predetermined sentiment classifications, applying a trained machine learning system to select a category from a set of predefined categories for each of the one or more comments, applying a natural language processing module to generate a sub-category for each of the one or more comments, associating the generated sub-categories with their respective categories for the one or more comments, and generating a display of the determined categories for the particular transaction with the generated sub-categories, each generated sub-category being graphically connected to their respective categories.

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