METHOD AND APPARATUS FOR KNOWLEDGE GRAPH CONSTRUCTION, STORAGE MEDIUM, AND ELECTRONIC DEVICE

    公开(公告)号:US20240330373A1

    公开(公告)日:2024-10-03

    申请号:US18573944

    申请日:2022-08-12

    Applicant: Lemon Inc.

    CPC classification number: G06F16/90344

    Abstract: The disclosure relates to a method and apparatus for knowledge graph construction, a storage medium, and an electronic device. The method comprises: obtaining a target entity identifier and determining an industry type label corresponding to the target entity identifier; determining a target industry attribute table based on a predetermined correspondence among the industry type label, an industry type, and an industry attribute table; obtaining target attribute values of the target entity identifier from a public database based on respective target attribute names in the target industry attribute table, to obtain a target attribute of the target entity identifier, wherein the target attribute characterizes a key-value pair consisting of the target attribute name and the target attribute value; and constructing a knowledge graph based on an entity characterized by the target entity identifier, the industry type label, and the target attribute.

    METHOD FOR FEATURE CONSTRUCTION, METHOD FOR CONTENT DISPLAY AND RELATED APPARATUS

    公开(公告)号:US20240289406A1

    公开(公告)日:2024-08-29

    申请号:US18563312

    申请日:2022-04-28

    Applicant: Lemon Inc.

    CPC classification number: G06F16/9574

    Abstract: The present disclosure relates to a method for feature construction, a method for content display and a related apparatus. The method for feature construction comprises: acquiring interaction data on a content page and loading performance data of the content page; constructing a user interaction feature according to the interaction data on the content page, and constructing a page performance feature of the content page according to the loading performance data of the content page. The user interaction feature and the page performance feature are used for training a content display model, and the content display model is used for determining target content displayed to a target user.

    MEDIA DATA MANAGEMENT IN SOCIAL APPLICATION
    3.
    发明公开

    公开(公告)号:US20240202836A1

    公开(公告)日:2024-06-20

    申请号:US18068345

    申请日:2022-12-19

    Applicant: Lemon Inc.

    CPC classification number: G06Q50/01 G06F3/0481 G06F16/24575

    Abstract: There are provided methods, devices, and computer program products for providing media data in a social application. In the method, a first user account of the social application is determined, and the first user account is a business user account of the social application. An interaction event is obtained between a second user account of the social application and the first user account, and the second user account being a personal user account of the social application. Media data associated with the first user account is provided to the second user account based on the interaction event. With these implementations, the data communications between the business user account and the personal user account may be implemented in a flexible and effective way.

    METHOD AND APPARATUS FOR KNOWLEDGE GRAPH CONSTRUCTION, STORAGE MEDIUM, AND ELECTRONIC DEVICE

    公开(公告)号:US20240135196A1

    公开(公告)日:2024-04-25

    申请号:US18397227

    申请日:2023-12-27

    Applicant: Lemon Inc.

    CPC classification number: G06N5/02

    Abstract: The present disclosure relates to a method and apparatus for knowledge graph construction, storage medium and electronic device. The method for knowledge graph construction, comprises: identifying an entity concept from a title text of a target web page and at least one entity corresponding to the entity concept from a body text of the target web page; constructing a syntax parse tree of the title text based on syntax parse rules of a language to which the title text belongs, and determining, from the syntax parse tree, a modifier for modifying the entity concept; and generating a knowledge graph based on the entity concept, the modifier, and the at least one entity. Through the solution of the present disclosure, knowledge graphs with high accuracy and high recall rates are constructed without structured processing on target web pages.

    ATTRIBUTE AND RATING CO-EXTRACTION
    5.
    发明公开

    公开(公告)号:US20230342553A1

    公开(公告)日:2023-10-26

    申请号:US17727015

    申请日:2022-04-22

    Applicant: LEMON INC.

    CPC classification number: G06F40/30 G06F40/279 G06N3/0454

    Abstract: Embodiments of the present disclosure relate to attribute and rating co-extraction. According to embodiments of the present disclosure, a method is proposed. The method comprises: determining, by a first sub-network of a model, a first feature representation based on a first token contained in a text, the first feature representation indicating semantic information of the first token in the text; determining, by a second sub-network of the model, first attribute information associated with the first token based on the first feature representation, the first attribute information indicating a first attribute involved in the text; and determining, by a third sub-network of the model, first rating information associated with the first token based on the first feature representation, the first rating information indicating a rating related to the first attribute.

    FEATURE MANAGEMENT
    7.
    发明申请

    公开(公告)号:US20250036937A1

    公开(公告)日:2025-01-30

    申请号:US18359643

    申请日:2023-07-26

    Applicant: Lemon Inc.

    Abstract: There are proposed methods, devices, and computer program products for feature management. In the method, a first event associated with a first and a second object, and a second event associated with the first and second events are obtained, and a type of the first event is different from a type of the second event. A first feature of the first object is determined based on a first encoder, and a second feature of the second object is determined based on a second encoder. The first encoder is updated based on the first and second features and the first and second events. With these implementations, multiple events are used in determining the encoder for extracting the feature, and thus the encoder may have better performance in accuracy and increase performance of downstream tasks.

    WEB PAGE CLASSIFICATION METHOD, APPARATUS, STORAGE MEDIUM AND ELECTRONIC DEVICE

    公开(公告)号:US20240289394A1

    公开(公告)日:2024-08-29

    申请号:US18572097

    申请日:2022-06-02

    Applicant: Lemon Inc.

    CPC classification number: G06F16/906 G06F16/9535 G06F16/958

    Abstract: The present disclosure relates to a web page classification method, apparatus, storage medium, and electronic device. The method comprises: acquiring feature information of a web page to be classified; respectively predicting, according to each piece of the feature information, a candidate web page category of the web page to be classified; and determining, from all the candidate web page categories, a target web page category to which the web page to be classified belongs. The candidate web page category of the web page to be classified is predicted by using various feature information of the web page to be classified, and the target web page category of the web page to be classified is further determined from the candidate web page categories, thereby improving the accuracy of web page classification.

    SPEECH TENDENCY CLASSIFICATION
    9.
    发明公开

    公开(公告)号:US20230377560A1

    公开(公告)日:2023-11-23

    申请号:US17747704

    申请日:2022-05-18

    Applicant: Lemon Inc.

    CPC classification number: G10L15/02 G10L15/04 G10L17/00 G10L25/90

    Abstract: Embodiments of the present disclosure relate to speech tendency classification. According to embodiments of the present disclosure, a method comprises extracting, from a speech segment, voiceprint information and at least one of volume information or speaking rate information; determining, based on the voiceprint information, first probability information indicating respective first probabilities of a plurality of tendency categories into which the speech segment is classified; determining, based on the at least one of the volume information or the speaking rate information, second probability information indicating respective second probabilities of the plurality of tendency categories into which the speech segment is classified; and determining, based at least in part on the first probability information and the second probability information, target probability information for the speech segment, the target probability information indicating respective target probabilities of the plurality of tendency categories into which the speech segment is classified.

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