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Joint extraction of biomedical overlapping triples through feature partition encoding

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成果类型:
期刊论文
作者:
Zhu, Qiang;Hong, Cheng;Meng, Yajie;Yang, Huali;Zhao, Weizhong
通讯作者:
Zhu, Q
作者机构:
[Zhu, Qiang; Meng, Yajie; Yang, Huali] Wuhan Text Univ, Sch Comp Sci & Artificial Intelligence, Wuhan, Hubei, Peoples R China.
[Zhu, Qiang; Meng, Yajie; Hong, Cheng; Yang, Huali] Engn Res Ctr Hubei Prov Clothing Informat, Wuhan, Hubei, Peoples R China.
[Zhao, Weizhong] Cent China Normal Univ, Sch Comp Sci, Wuhan, Hubei, Peoples R China.
通讯机构:
[Zhu, Q ] W
Wuhan Text Univ, Sch Comp Sci & Artificial Intelligence, Wuhan, Hubei, Peoples R China.
语种:
英文
关键词:
Entities and relations extraction;The overlapping triple problem;Feature partition encoding;Relative positional embedding
期刊:
Expert Systems with Applications
ISSN:
0957-4174
年:
2024
卷:
241
页码:
122723
机构署名:
本校为其他机构
院系归属:
计算机学院
摘要:
Entities and relations extraction are the key tasks in the construction of biomedical knowledge graph, which play an important role in the biomedical artificial intelligence. However, extraction of entities and relations from biomedical texts is challenging because of the overlapping triples problem. The previous approaches typically divided the task into two separate sub-tasks. However, these methods failed to address the error propagation problem. Recent methods have been proposed to perform both sub-tasks simultaneously. Nonetheless, most current methods still encounter issues related to im...

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