為了達到有效的知識管理及運用，實體論的技術漸漸的被廣泛地應用在不同的知識領域裡。本論文旨在發展一個實體論的自動建構技術，以幫助知識管理者自動地建構出理想的知識系統。首先，我們提出一套物件導向的模式來表現出實體論的架構，稱之為具物件導向式之實體論，並依據此模式的建構程序來發展實體論自動建構技術。其次，利用中研院所提供之CKIP系統來進行中文文件之斷詞及詞性標注，再利用本論文所提出之特徵詞選取機制從已加注詞性之中文文件中選出重要的特徵詞。再來，本文提出二種自動建構Domain Ontology中之Concept的方法，包括SOM機制及Fuzzy Compatibility Relation技術。在建構的過程中，採用資料探勘、模糊推論機制及模糊聚類等技術來達成建構的自動化。最後，我們提出一個基於實體論架構之資訊分類方法。經由實驗証實，本方法能對網路文件有效地進行自動分類。

In order to efficiently manage and use knowledge, the technologies of ontology are widely applied to various kinds of domain knowledge. This thesis proposes an automatic ontology construction approach that can help knowledge manager efficiently construct a domain knowledge. The first feature of this thesis is to utilize an object-oriented approach to represent the structure of ontology, called object-oriented ontology. Second, the automatic ontology construction approach for Chinese News domain is presented. We embed CKIP system to carry out the Chinese natural language processing including part-of-speech tagging, Chinese-Term analysis and Chinese-Term feature selection. Third, the concept clustering mechanisms for domain ontology construction based on SOM clustering technology and fuzzy compatibility relation approach are proposed in this thesis, respectively. Furthermore, the parallel fuzzy inference mechanism is also adopted to infer the conceptual resonance strength of any two Chinese terms. Finally, we propose a new information classification model based on the constructed ontology. The experimental results exhibit that the proposed approach can classify the Internet documents effectively.

[1] D. Fensel, “The Semantic Web and Its Languages,” IEEE Intelligent Systems, pp. 67-73, Nov./Dec., 2000.
[2] P.E. van der Vet and N.J.I. Mars, “Bottom-Up Construction Ontologies,” IEEE Trans. on Knowledge and data Engineering, Vol. 10, No. 4, pp.513-526, July/August, 1998.
[3] N. Guarino, “Formal Ontology and Information System,” Proc. of the First International Conference (FOIS'98), Trento, Italy, June, 1998.
[4] G. Van Heijst, A. Th. Schreiber and B.J. Wielinga, “Using explicit ontologies in KBS development,” International Journal of Human–Computer Studies, Vol. 46, pp. 183–292, 1997.
[5] N. Guarino, “Understanding, Building and Using Ontologies,” International Journal of Human-Computer Studies, Vol. 46, pp. 293-310, 1997.
[6] T.R. Gruber, “ONTOLINGUA: A Mechanism to Support Portable Ontologies,” Technical Report, Knowledge Systems Laboratory, Stanford University, Stanford, United States, 1992.
[7] B. J. Wielinga and A. Th. Schreiber, “Reusable and shareable knowledge bases: A european perspective,” In Proceedings International Conference on Building and Sharing of Very Large-Scaled Knowledge Bases '93, Japan Informtation Processing Development Center, Tokyo, Japan, Dec., 1993, pp. 103-115.
[8] Y.A. Tijerino and R. Mizoguchi, “MULTIS II: Enabling End Users to Design Problem Solving Engines Via two-level task ontologies,” In Lecture Notes in Artificial Intelligence 723: Knowledge Acquisition for Knowledge-Based Systems, Caylus, France, 1993, pp. 340-359.
[9] N. Guarino. “The Role of Identity Conditions in Ontology Design,” Lecture Notes in Computer Science, Vol. 1661, pp. 221-234, 1999.
[10] A. Gomez-Perez and O. Corcho, “Ontology Languages for the Semantic Web,” IEEE Intelligent Systems, pp. 54-60, Jan./Feb., 2002.
[11] P.D. Karp, V.K. Chaudhri and J. Thomere, “XOL: An XML-Based Ontology Exchange Language,” Technical Report, Articial Intelligence Center, SRI International, Aug., 1999. www.ai.sri.com/~pkarp/xol.
[12] S. Luke and J. Heflin, SHOE 1.01 Proposed Specification, SHOE Project, Feb. 2002. www.cs.umd.edu/projects/plus/SHOE/spec1.01htm.
[13] R. Kent, Conceptual Knowledge Markup Language (version 0.2). 1998. www.ontologos.org/CKML/CKML%200.2.html.
[14] O. Lassila and R. Webick, “Resource Description framework (RDF) Model and Syntax Specification.” W3C Recommendation, Jan. 1999, www.w3.org/TR/PR-rdf-syntax.
[15] D. Brickley and R.V. Guha, “Resource Description framework (RDF) Schema Specification,” W3C proposed Recommendation, Mar. 1999, www.w3.org/TR/PR-rdf-schema.
[16] D. Fensel, I. Horrocks, F. Van Harmelen, S. Decker, M. Erdmann and M. Klein, “OIL in a Nutshell,” 12th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2000), Juan-les-Pins, France, 2000, pp. 1-16.
[17] I. Horrocks and F. van Harmelen, Reference Description of the DAML+OIL Ontology Markup Language, draft report, 2001, www.daml.org/2000/12/reference.html (current Jan. 2002).
[18] Y. Li and A.K. Jain, “Classification of Text Documents,” The Computer Journal, Vol. 41, No. 8, pp. 537-546, 1998.
[19] P.S. Jacobes, “Using Statistical Methods to Improve Knowledge-Based News Categorization,” IEEE Expert, Vol. 8, No. 2, pp. 13-23, Apr., 1993.
[20] D. F. Specht, “Probabilistic neural networks,” Neural Networks, Vol. 3, pp. 109-118, 1990.
[21] J. Han and M. Kamber, Data Mining: Concepts and Techniques, New York: Morgan-Kaufman, 2001.
[22] L. Khan and F. Luo, “Ontology Construction for Information Selection,” Department of Computer Science University of Texas at Dallas, 2002.
[23] C. C. Kung, “Personalized XML Information Service System with Automatic Object-oriented Ontology Construction Capability,” Master, Thesis, Department of Computer Science & Information Engineering, National Cheng Kung University, Taiwan, June, 2001.
[24] S. Cranefield and M. Purvis, “UML as an Ontology Modeling Language,” Proc. of the Workshop on Intelligent Information Integration, 16th International Joint Conference on Artificial Intelligence (IJCAI-99), Stockholm, Sweden, July 31-August 6, 1999.
[25] “Academia Sinica Balanced Corpus,” Technical Report, No. 95-02/98-04, Academia Sinica, Taiwan, 1998.
[26] “Chinese Electronic Dictionary,” Technical Report, No. 93-05, Academia Sinica, Taiwan, 1993.
[27] “Chinese Electronic Dictionary,” Technical Report, No. 93-05, Academia Sinica, Taiwan, 1993.
[28] Y. H. Kuo, J. P. Hsu and C. W. Wang, “A Parallel Fuzzy Inference Model with Distributed Prediction Scheme for Reinforcement Learning,” IEEE Trans. on Systems, Man, and Cybernetics, Vol. 28, No. 2, pp.160-172, April, 1998.
[29] H. H. Chang, “Event Detection Driven Approach for Extracting Information from Internet Documents,” Master, Thesis, Department of Computer Science & Information Engineering, National Cheng Kung University, Taiwan, June, 2000.
[30] Y. J. Yang, et al., “An intelligent and efficient word-class-based Chinese language model for Mandarin speech recognition with very large vocabulary.” Proc. of ICSLP-94, Yokohama, Japan, 1994, pp. 1371-1374.
[31] J. Gao, J. T. Goodman and J. Miao, “The Use of Clustering Techniques for Language Modeling – Application to Asian Language,” Computational Linguistics and Chinese Language Processing , Vol. 6, No. 1, pp. 27-60, February, 2001.
[32] G.J. Klir, B. Yuan, Fuzzy Sets and Fuzzy Logic: Theory and Applications, New York: Binghamton, 1995.
[33] R. C. T. Lee, R. C. Chang, S. S. Tseng and Y. T. Tsai, Introduction to the Design and Analysis of Algorithms, Taipei, Unalis co., 1999.