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Extracting method knowledge elements from scientific literature: A rule‐based approach
Author(s) -
Wang Zhongyi,
Shen Xueying,
Huang Rong,
Huang Jing
Publication year - 2019
Publication title -
proceedings of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.193
H-Index - 14
ISSN - 2373-9231
DOI - 10.1002/pra2.183
Subject(s) - computer science , knowledge extraction , data mining , knowledge base , extraction (chemistry) , knowledge based systems , precision and recall , information retrieval , artificial intelligence , chromatography , chemistry
Knowledge elements are the basic unit of knowledge. Extracting knowledge elements from literatures enables granular knowledge organization and retrieval. This paper proposes a rule‐based framework for extracting method Knowledge Elements (KEs) in scientific literature aiming to improve the accuracy and complete extraction of method KEs. The method is divided into two stages: semi‐automated extraction of initial description rules of method KEs and automated derivation of additional description rules. In a preliminary evaluation on 415 papers, the precision and recall for the method KEs extraction are 0.77 and 0.84, respectively, indicating the effectiveness of our method.