Data Analysis and Knowledge Discovery  2021, Vol. 5 Issue (4): 123-133    DOI: 10.11925/infotech.2096-3467.2020.0794
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Extraction and Representation of Domain Knowledge with Semantic Description Model and Knowledge Elements——Case Study of Information Retrieval
Shi Xiang,Liu Ping()
School of Information Management, Wuhan University, Wuhan 430072, China
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Abstract

[Objective] This paper tries to extract and integrate domain knowledge from heterogeneous data based on knowledge elements, aiming to enrich the semantic information of knowledge representation. [Methods] We proposed a new method to extract and represent knowledge based on the semantic description model with knowledge elements. Then, we examined our model in the field of information retrieval. [Results] We extracted 4,200 knowledge elements and 3,020 entities on information retrieval from Wikipedia and two classic textbooks. We could query the relationship between knowledge elements and their entities. [Limitations] The semantic relations among knowledge elements were not adequately explored, and the process of knowledge extraction was not fully automated. [Conclusions] This paper improves the semantics of knowledge representation, and provides new perspectives for domain knowledge service.

Received: 17 August 2020      Published: 24 November 2020
 ZTFLH: 分类号: TP182
Fund:National Natural Science Foundation of China(71573196)
Corresponding Authors: Liu Ping     E-mail: pliuleeds@126.com