RMAN: Relational multi-head attention neural network for joint extraction of entities and relations
Sign Up to like & getrecommendations! Published in 2022 at "Applied Intelligence"
DOI: 10.1007/s10489-021-02600-2
Abstract: The task of extracting entities and relations has evolved from distributed extraction to joint extraction. The joint model overcomes the disadvantages of distributed extraction method and strengthens the information interaction between entities and relations. However,… read more here.
Keywords: extraction entities; joint extraction; attention; entities relations ... See more keywords
Joint extraction of entities and relations by a novel end-to-end model with a double-pointer module
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.09.097
Abstract: Abstract Joint extraction of entities and relations is to detect entities and recognize semantic relations simultaneously. However, some existing joint models predict relations on words, instead of entities. These models cannot make full use of… read more here.
Keywords: extraction; end; pointer module; entities relations ... See more keywords
GUniER: GPT-Enhanced Joint Extraction of Entities and Relations Through Integrated Deep Bidirectional Semantics and Unified Modeling
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3512553
Abstract: Entity and relation extraction are key tasks in natural language processing (NLP) and knowledge graph construction. However, existing methods often overlook the complex interactions between entities and their relations. To address this problem, we propose… read more here.
Keywords: semantics; extraction entities; entities relations; deep bidirectional ... See more keywords
Joint Extraction of Entities and Relations Using Reinforcement Learning and Deep Learning
Sign Up to like & getrecommendations! Published in 2017 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2017/7643065
Abstract: We use both reinforcement learning and deep learning to simultaneously extract entities and relations from unstructured texts. For reinforcement learning, we model the task as a two-step decision process. Deep learning is used to automatically… read more here.
Keywords: extraction; learning; entities relations; deep learning ... See more keywords
Joint extraction of Chinese medical entities and relations based on RoBERTa and single-module global pointer
Sign Up to like & getrecommendations! Published in 2024 at "BMC Medical Informatics and Decision Making"
DOI: 10.1186/s12911-024-02577-1
Abstract: Most Chinese joint entity and relation extraction tasks in medicine involve numerous nested entities, overlapping relations, and other challenging extraction issues. In response to these problems, some traditional methods decompose the joint extraction task into… read more here.
Keywords: joint extraction; global pointer; entities relations; extraction ... See more keywords
Mining of Textual Health Information from Reddit: Analysis of Chronic Diseases With Extracted Entities and Their Relations
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Medical Internet Research"
DOI: 10.2196/12876
Abstract: Background Social media platforms constitute a rich data source for natural language processing tasks such as named entity recognition, relation extraction, and sentiment analysis. In particular, social media platforms about health provide a different insight… read more here.
Keywords: social media; chronic diseases; extracted entities; entities relations ... See more keywords