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.

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.

公开(公告)号：US20220319500A1

公开(公告)日：2022-10-06

申请号：US17425211

申请日：2021-07-08

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Taewoo LEE ,  Taegyoon KANG ,  Hogyeong KIM ,  Minjoong LEE ,  Seokyeong JUNG ,  Jiseung JEONG

IPC: G10L15/16 ,  G10L15/18 ,  G10L15/06

Abstract: Disclosed is an electronic device including processor and memory operatively connected to the processor and storing language model. The electronic device may enter data into the language model, generate an embedding vector in the input embedding layer, add position information to the embedding vector in the positional encoding layer, branch the embedding vector based on domain information, normalize the branched embedding vectors, enter the normalized embedding vectors into the multi-head attention layer, enter output data of the multi-head attention layer into the first layer, normalize pieces of output data of the first layer, enter the normalized pieces of output data of the first layer into the feed-forward layer, enter output data of the feed-forward layer into the second layer and normalize pieces of output data of the second layer, and enter the normalized pieces of output data of the second layer into the linearization layer and the softmax layer to obtain result data. In addition, various embodiments as understood from the specification may be also possible.