A Chinese Term Clustering Mechanism for Generating Semantic Concepts of a News Ontology

Chang-Shing Lee ； Yau-Hwang Kuo ； Chia-Hsin Liao ； Zhi-Wei Jian

《中文計算語言學期刊》 10卷2期 (2005/07) Pp. 277-302

https://doi.org/10.30019/IJCLCLP.200507.0007

並列摘要

In order to efficiently manage and use knowledge, ontology technologies are widely applied to various kinds of domain knowledge. This paper proposes a Chinese term clustering mechanism for generating semantic concepts of a news ontology. We utilize the parallel fuzzy inference mechanism to infer the conceptual resonance strength of a Chinese term pair. There are four input fuzzy variables, consisting of a Part-of-Speech (POS) fuzzy variable, Term Vocabulary (TV) fuzzy variable, Term Association (TA) fuzzy variable, and Common Term Association (CTA) fuzzy variable, and one output fuzzy variable, the Conceptual Resonance Strength (CRS), in the mechanism. In addition, the CKJP tool is used in Chinese natural language processing tasks, including POS tagging, refining tagging, and stop word filtering. The fuzzy compatibility relation approach to the semantic concept clustering is also proposed. Simulation results show that our approach can effectively cluster Chinese terms to generate the semantic concepts of a news ontology.

並列關鍵字

Ontology ； Chinese Natural Language Processing ； Fuzzy Inference ； Feature Selection ； Concept Clustering

參考文獻

Gao, J.,J. T. Goodman,J. Miao(2001).The Use of Clustering Techniques for Language Modeling-Application to Asian Language.(Computational Linguistics and Chinese Language Processing).

Alani, H.,S. Kim,D. E. Millard,M. J. Weal,W. Hall,P. H. Lewis,N. R. Shadbolt(2003).Automatic Ontology-Based Knowledge Extraction from Web Documents,.(IEEE Intelligent Systems).

CKIP(1998).Academia Sinica Balanced Corpus, Technical Report, No. 95-02/98-04.

CKIP(1993).Chinese Electronic Dictionary, Technical Report, No. 93-05.

Embley, D. W.,D. M. Campbell,R. D. Smith,S. W. Liddles(1998).Ontology-based extraction and structuring of information from data-rich unstructured documents.(Proceeding Of ACM Conference on Information and Knowledge Management).