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    METHOD AND APPARATUS WITH ENTITY LINKING
    1.
    发明公开
    METHOD AND APPARATUS WITH ENTITY LINKING 审中-公开

    公开(公告)号：US20240176806A1

    公开(公告)日：2024-05-30

    申请号：US18464689

    申请日：2023-09-11

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Jangsu LEE ,  Jehun JEON ,  Jiseung JEONG ,  Inkyu CHOI ,  GyuBum HAN

    IPC: G06F16/33

    CPC classification number: G06F16/334

    Abstract: Disclosed is an entity linking method. A method includes: extracting an entity from an input context including text stored in a memory; obtaining candidate entities corresponding to, and based on, the extracted entity; determining a keyword based on the input context; generating keyword-based entity information based on the keyword and based on the extracted entity; and determining a top-matching entity corresponding to the entity based on the keyword-based entity information and the plurality of candidate entities.

    METHOD AND DEVICE WITH NATURAL LANGUAGE PROCESSING
    2.
    发明申请
    METHOD AND DEVICE WITH NATURAL LANGUAGE PROCESSING 有权

    公开(公告)号：US20220092266A1

    公开(公告)日：2022-03-24

    申请号：US17186830

    申请日：2021-02-26

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Inkyu CHOI ,  Jehun JEON ,  GyuBum HAN

    IPC: G06F40/30 ,  G06N3/08 ,  G06N5/02

    Abstract: A method and device with natural language processing is disclosed. The method includes performing a word embedding of an input sentence, encoding a result of the word embedding, using an encoder of a natural language processing model, to generate a context embedding vector, decoding the context embedding vector, using a decoder of the natural language processing model, to generate an output sentence corresponding to the input sentence, generating a score indicating a relationship between the context embedding vector and each of a plurality of knowledge embedding vectors, determining a first loss based on the output sentence, determining a second loss based on the generated score, and performing training of the natural language processing model, including training the natural language processing model based on the determined first loss, and training the natural language processing model based on the determined second loss.

    METHOD AND DEVICE WITH EXPANDING KNOWLEDGE GRAPH
    3.
    发明公开
    METHOD AND DEVICE WITH EXPANDING KNOWLEDGE GRAPH 审中-公开

    公开(公告)号：US20240232579A1

    公开(公告)日：2024-07-11

    申请号：US18524053

    申请日：2023-11-30

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： GyuBum HAN ,  Jehun JEON ,  Jangsu LEE ,  Jiseung JEONG ,  Inkyu CHOI

    IPC: G06N3/045 ,  G06N3/048

    CPC classification number: G06N3/045 ,  G06N3/048

    Abstract: A method of expanding a knowledge graph and an electronic device for performing the method are provided. The electronic device includes a processor and the processor is configured to train a first neural network to extract the triplet using the training data, to compare quality of the trained first neural network to a threshold value using the validation data, to extract a new triplet by inputting the text data to the trained first neural network, to measure a first confidence of the new triplet using the trained first neural network, to measure a second confidence of the new triplet using a trained second neural network using a triplet labeled to the training data and a triplet labeled to the validation data, and to expand the knowledge graph based on the first confidence and the second confidence.

    METHOD AND APPARATUS FOR MODELING USER PREFERENCES
    4.
    发明申请
    METHOD AND APPARATUS FOR MODELING USER PREFERENCES 有权

    公开(公告)号：US20230126117A1

    公开(公告)日：2023-04-27

    申请号：US17698667

    申请日：2022-03-18

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Jehun JEON ,  Jangsu LEE ,  Inkyu CHOI ,  GyuBum HAN

    IPC: G06F16/9535

    Abstract: A user preference modeling method including receiving preference scores corresponding to items, receiving an input for selecting an item from among the items, decaying a preference score corresponding to one or more items from among the items included in a first list and a second list based on a time decay rate and a first parameter, in response to the selected item being included in the first list, decaying the preference score corresponding to the one or more items comp included in the first list and the second list based on a time decay rate and a second parameter, in response to the selected item being included in the second list, and increasing a preference score corresponding to the selected item, wherein the first list may include one or more of the plurality of items based on the preference scores, and wherein the first list is different from the second list.

    METHOD AND APPARATUS FOR TRAINING EMBEDDING VECTOR GENERATION MODEL
    5.
    发明申请
    METHOD AND APPARATUS FOR TRAINING EMBEDDING VECTOR GENERATION MODEL 有权

    公开(公告)号：US20220058433A1

    公开(公告)日：2022-02-24

    申请号：US17153011

    申请日：2021-01-20

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： GyuBum HAN ,  Jehun JEON ,  Inkyu CHOI

    IPC: G06K9/62 ,  G06F40/295 ,  G06F40/30

    Abstract: A method and apparatus for training an embedding vector generation model are provided, the method includes identifying a keyword in a query sentence, generating an embedding vector of the query sentence and an embedding vector of the keyword based on the embedding vector generation model, and training the embedding vector generation model such that a first similarity between the embedding vector of the query sentence and the embedding vector of the keyword is greater than a second similarity between an embedding vector of a reference sentence that does not include the keyword and the embedding vector of the keyword.

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