Results 31 to 40 of about 1,302,763 (303)

CID-GCN: An Effective Graph Convolutional Networks for Chemical-Induced Disease Relation Extraction

Frontiers in Genetics, 2021
Automatic extraction of chemical-induced disease (CID) relation from unstructured text is of essential importance for disease treatment and drug development.
Daojian Zeng, Chao Zhao, Zhe Quan
doaj   +1 more source

Document-Level Relation Extraction with Relation Correlation Enhancement

, 2023
Document-level relation extraction (DocRE) is a task that focuses on identifying relations between entities within a document. However, existing DocRE models often overlook the correlation between relations and lack a quantitative analysis of relation correlations.
Huang, Yusheng, Lin, Zhouhan
openaire   +2 more sources

Extracting Relations Between Sectors

2022 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), 2022
The term "sector" in professional business life is a vague concept since companies tend to identify themselves as operating in multiple sectors simultaneously. This ambiguity poses problems in recommending jobs to job seekers or finding suitable candidates for open positions.
Daniş, Fahri Serhan, Turhan, Sultan Nezihe, Orman, Gunce Keziban, Kara, Atakan   +3 more
openaire   +3 more sources

Dialogue-Based Relation Extraction [PDF]

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020
To appear in ACL ...
Yu, Dian, Sun, Kai, Cardie, Claire, Yu, Dong   +3 more
openaire   +2 more sources

An Attention-Based Model Using Character Composition of Entities in Chinese Relation Extraction

Information, 2020
Relation extraction is a vital task in natural language processing. It aims to identify the relationship between two specified entities in a sentence. Besides information contained in the sentence, additional information about the entities is verified to
Xiaoyu Han, Yue Zhang, Wenkai Zhang, Tinglei Huang   +3 more
doaj   +1 more source

GOF/LOF knowledge inference with tensor decomposition in support of high order link discovery for gene, mutation and disease

Mathematical Biosciences and Engineering, 2019
For discovery of new usage of drugs, the function type of their target genes plays an important role, and the hypothesis of "Antagonist-GOF" and "Agonist-LOF" has laid a solid foundation for supporting drug repurposing.
Kaiyin Zhou, YuxingWang, Sheng Zhang , Mina Gachloo, Jin-Dong Kim , Qi Luo, Kevin Bretonnel Cohen, Jingbo Xia   +7 more
doaj   +1 more source

Research on the Chinese Named-Entity–Relation-Extraction Method for Crop Diseases Based on BERT

Agronomy, 2022
In order to integrate fragmented text data of crop disease knowledge to solve the current problems of disordered knowledge management, weak correlation and difficulty in knowledge sharing, a Chinese named-entity–relation-extraction model for crop ...
Wenhao Zhang, Chunshan Wang, Huarui Wu, Chunjiang Zhao, Guifa Teng, Sufang Huang, Zhen Liu   +6 more
doaj   +1 more source

Using Neural Networks for Relation Extraction from Biomedical Literature

, 2020
Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems.
A Koike, A Lamurias, A Lamurias, A Lamurias, A Lamurias, A Singhal, AV Aho, B Xu, CD Manning, CH Alves, D Westergaard, D Zhou, E Guresen, F Rinaldi, HC Wang, HM Müller, J Hastings, L Aroyo, M Ashburner, MY Kim, N Ma, N Peng, P Goyal, P Zweigenbaum, PN Robinson, Q Li, QL Nguyen, S HayKin, S Hochreiter, TR Gruber, W Wang, WWM Fleuren, Y Hao, Y Luo, Y Xu   +34 more
core   +1 more source

Modeling Relation Paths for Representation Learning of Knowledge Bases [PDF]

, 2015
Representation learning of knowledge bases (KBs) aims to embed both entities and relations into a low-dimensional space. Most existing methods only consider direct relations in representation learning.
Lin, Yankai, Liu, Song, Liu, Zhiyuan, Luan, Huanbo, Rao, Siwei, Sun, Maosong   +5 more
core   +2 more sources

Application of Public Knowledge Discovery Tool (PKDE4J) to Represent Biomedical Scientific Knowledge

Frontiers in Research Metrics and Analytics, 2018
In today’s era of information explosion, extracting entities and their relations in large-scale, unstructured collections of text to better represent knowledge has emerged as a daunting challenge in biomedical text mining.
Min Song, Munui Kim, Keunyoung Kang, Yong Hwan Kim, Sieun Jeon   +4 more
doaj   +1 more source