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| Methods of Extracting Non-Categorical Semantic Relations between Chinese Terms |
| Zhu Hui1, 2, Wang Hao1, 2, Su Xinning1, 2, Deng Sanhong1, 2 |
1. School of Information Management, Nanjing University, Nanjing 210023;
2. Jiangsu Key Laboratory of Data Engineering and Knowledge Services, Nanjing University, Nanjing 210023 |
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Abstract Ontology is an effective method of knowledge organization, and it is also the important link in constructing the Semantic Web. The non-categorical semantic relations between concepts are important parts of ontology. Because the term is the external expression of a concept, this paper introduces co-occurrence, structural analysis, template construction, logical reasoning, and other methods to construct a model that can extract non-categorical semantic relations between terms from Chinese unstructured texts. The model extracts the relations from two different perspectives: content and structure. The paper puts forward the main operation flow of the model and the main components of each functional module, discusses the specific realization of the main components, and discusses the limitations of the methods. The research will provide new ideas for the extraction of non-categorical semantic relations between terms, enrich the methods of knowledge discovery, and provide references for the implementation of feasible and effective knowledge organization.
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Received: 15 October 2018
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