在許多資訊系統及語意網(Semantic Web)中Ontology扮演極重要的角色，因它能描述領域知識內的概念與關係，而領域知識通常是從文件中衍生出來的，故文件內的知識呈現與應用性實為重要的研究議題。本論文中，我們應用Ontology特性表達中文需求文件與中文新聞文件之特定領域知識，以期完成需求追溯與中文文件摘要等工作。對於中文需求文件的處理，我們提出一“基於Ontology之需求追溯代理人”，針對中文需求文件經由概念轉換、關聯生成、關聯權重生成與追溯Ontology生成等處理程序建構Traceability Ontology，以便需求追溯代理人能依據追溯知識結構於需求變更時，能完整且精確地分析其衍生影響；對於中文新聞文件的處理，我們提出一“基於Fuzzy Ontology之中文文件摘要”，首先透過文件前置處理機制與詞彙分類取得中文新聞文件之詞彙集合，接著運用模糊推論機制轉換Domain Ontology為Fuzzy Ontology，最後由中文文件摘要代理人參考Fuzzy Ontology，進行文件前置處理機制、模糊推論機制、基因學習機制、語句路徑生成、語句生成與語句過濾等處理程序，以完成中文文件摘要的處理。經由實驗驗證，本論文所提出之方法能有效地進行需求變更時的追溯及影響分析與中文文件摘要處理。

　Due to the fact that an ontology can describe the specific domain knowledge with the concepts and relationships and play an important role in many information systems and Semantic Web, therefore a great deal of the specific domain knowledge deriving from the documents in which knowledge represents and applies will be an important research topic. In this thesis, we adopt the characteristic of the ontology to describe the domain-specific knowledge of Chinese documents to achieve requirement tracking and Chinese document summarization tasks. With regard to the process of Chinese requirement document we propose a method, Ontology-based Requirements Traceability Agent, adopts Concept Transformation, Relation Generator, Relation Weight Generator, and Traceability Ontology Generator with Chinese requirement document to construct a Traceability Ontology. As requirements may change, the Requirements Traceability Agent can effectively analyze the impact of the changes according to the structure of traceability knowledge. With regard to the process of Chinese news document we propose a method, Fuzzy Ontology-based Chinese document Summarization, first derives term set of Chinese news document from Document Preprocessing Mechanism, and Term Classifier, and then utilizes the Fuzzy Inference Mechanism to transform a Domain Ontology into a Fuzzy Ontology. Finally, the Chinese Document Summarization Agent refers to Fuzzy Ontology to address Document Preprocessing Mechanism, Fuzzy Inference Mechanism, Genetic Learning Mechanism, Sentence Path Generator, Sentence Generator, and Sentence Filter to deal with document summarization. The experimental results show that our approach can effectively address impact analysis during the requirements of the changes and Chinese document summarization.

[1] H. Alani, S. Kim, D. E. Millard, M. J. Weal, W. Hall, P. H. Lewis, and N. R. Shadbolt, “Automatic ontology-based knowledge extraction from web documents,” IEEE Intelligent Systems, vol. 18, no. 1, pp. 14-21, Jan./Feb. 2003.
[2] J. Casillas, O. Cordón, F. Herrera, and M. J. D. Jesus, “Genetic tuning of fuzzy rule-based systems integrating linguistic hedges,” in Proc. of IFSA World Congress and 20th NAFIPS International Conference, 2001, pp. 1570-1574.
[3] Chinese Knowledge Information Processing Group, Academic sinica. (1998) CKIP AutoTag. [Online]. Available e-mail: eddie@hp.iis.sinica.edu.tw
[4] T. H. Cormen, C. E. Leiserson, and R. L. Rivest, Introduction to Algorithms. New York: McGraw-Hill, 1999.
[5] J. N. O. Dag, B. Regnell, V. Gervasi, and S. Brinkkemper, “A linguistic-engineering approach to large-scale requirements management,” IEEE Software, vol. 22, no. 1, pp. 32-39, Jan./Feb. 2005.
[6] D. W. Embley, D. M. Campbell, R. D. Smith, and S. W. Liddle, “Ontology-based extraction and structuring of information from data-rich unstructured documents,” in Proc. of ACM Conference on Information and Knowledge Management, USA, 1998, pp. 52-59.
[7] D. Fensel, “Ontology-based knowledge management,” IEEE Computer, vol. 35, no. 11, pp. 56-59, Nov. 2002.
[8] D. Fensel, “The semantic web and its languages,” IEEE Intelligence Systems, vol. 15, no. 6, pp. 67-73, Nov./Dec. 2000.
[9] J. Fiksel and M. Dunkle, “Principles of requirement management automation,” in Proc. of Reliability and Maintainability Computer-Aided Engineering in Concurrent Engineering, 1991, pp. 231-236.
[10] A Gómez-Pérez and O. Corcho, “Ontology languages for the semantic web,” IEEE Intelligence Systems, vol. 17, no. 1, pp. 54-60, Jan./Feb. 2002.
[11] Y. Gong and X. Liu, “Generic text summarization using relevance measure and latent semantic analysis,” in Proc. of the 24th annual international ACM SIGIR conference on Research and development in information retrieval, USA, 2001, pp. 19-25.
[12] T. R. Gruber, “A translation approach to portable ontology specifications,” Knowledge Acquisition, vol. 5, no. 2, pp. 199-220, 1993.
[13] N. Guarino, “Formal ontology and information systems,” in Proc. of the First International Conference (FOIS'98), Trento, Italy, 1998, pp. 3-15.
[14] N. Guarino, C. Masolo, and G. Vetere, “OntoSeek: content-based access to the web,” IEEE Intelligent Systems, vol. 14, no. 3, pp. 70-80, May/June 1999.
[15] U. Habn and I. Mani, “The challenges of automatic summarization,” IEEE Computer, vol. 33, no. 11, pp. 29-36, Nov. 2000.
[16] H. V. Halteren, “New feature sets for summarization by sentence extraction,” IEEE Intelligent Systems, vol. 18, no. 4, pp. 34-42, July/Aug. 2003.
[17] S. Handschuh, S. Staab, and F. Ciravegna, “S-CREAM-Semi-Automatic CREAtion of Metadata,” in Proc. of the 13th International Conference on Knowledge Engineering and Management (EKAW 2002), Spain, 2002, pp. 358-372.
[18] F. Herrera, M. Lozano, and J. L. Verdegay, “Fuzzy connectives based crossover operators to model genetic algorithms population diversity,” Fuzzy Sets and Systems, vol. 92, no. 1, pp. 21-30, Nov. 1997.
[19] M. Hoffmann, M. Kühn, M. Weber, and M. Bittner, “Requirements for requirements management tools,” in Proc. of the 12th IEEE International Requirements Engineering Conference, 2004, pp. 301-308.
[20] I. Horrocks, P. F. Patel-Schneider, and F. V. Harmelen, “From SHIQ and RDF to OWL: the making of a Web Ontology Language,” Web Semantics: Science, Services and Agents on the World Wide Web, vol. 1, no. 1, pp. 7-26, Dec. 2003.
[21] M. Jarke, “Requirements tracing,” Communications of the ACM, vol. 41, no. 12, pp. 32-36, Dec. 1998.
[22] G. Klyne, J. J. Carroll, and B. McBride. (2004, Feb.). Resource description framework (RDF): concepts and abstract syntax. [Online]. Available: http://www.w3.org/TR/rdf-concepts/
[23] J. Kupiec, J. Pedersen, and F. Chen, “A trainable document summarizer,” in Proc. of the 18th annual international ACM SIGIR conference on Research and development in information retrieval, 1999, pp. 68-73.
[24] W. Lam and K. S. Ho, “FIDS: an intelligent financial web news articles digest system,” IEEE Transaction on SMC-part A, vol. 31, no. 6, pp. 753-762, Nov. 2001.
[25] N. Lammari and E. Metais, “Building and maintaining ontologies: a set of algorithm,” Data & Knowledge Engineering, vol. 48, no. 2, pp. 155-176, Feb. 2004.
[26] C. S. Lee, C. P. Chen, H. J Chen, and Y. H. Kuo, “A fuzzy classification agent for personal e-news service”, International Journal of Fuzzy Systems, vol. 4, no. 4, pp. 849-856, Dec. 2002.
[27] C. S. Lee and C. Y. Pan, “An intelligent fuzzy agent for meeting scheduling decision support system,” Fuzzy Sets and Systems, vol. 142, no. 3, pp. 467-488, March 2004.
[28] C. S. Lee, J. X. Liao, and Y. H. Kuo, “A semantic-based concept clustering mechanism for Chinese news ontology construction”, in Proc. of International Computer Symposium, Taiwan, 2002.
[29] C. S. Lee, Y. J. Chen, and Z. W. Jian, “Ontology-based fuzzy event extraction agent for Chinese e-news summarization,” Expert Systems with Applications, vol. 25, no. 3, pp. 431-447, Oct. 2003.
[30] C. S. Lee, S. M. Guo, and C. Y. Hsu, “Genetic-based fuzzy image filter and its application to image processing,” IEEE Transactions on Systems, Man and Cybernetics Part B, vol. 35, no. 4, pp. 694-711, Aug. 2005.
[31] C. S. Lee, Z. W. Jian, and L. K. Huang, “A fuzzy ontology and its application to news summarization,” IEEE Transactions on Systems, Man and Cybernetics Part B, vol. 35, no. 5, pp. 859-880, Oct. 2005.
[32] C. T. Lin and C. S. G. Lee, “Neural-network-based fuzzy logic control and decision system,” IEEE Transactions on Computers, vol. 40, no. 12, pp. 1320-1336, Dec. 1991.
[33] D. Mallett, J. Elding, and M. A. Nascimento, “Information-content based sentence extraction for text summarization,” in Proc. of the International Conference on Information Technology: Coding and Computing (ITCC’04), 2004, pp. 214-218.
[34] K. F. Man, K. S. Tang, and S. Kwong, Genetic Algorithm. Hong Kong: Springer-Verlag, 1999.
[35] E. M. Maximilien and M. P. Singh, “A framework and ontology for dynamic web services selection,” IEEE Internet Computing, vol. 8, no. 5, pp. 84-93, Sept./Oct. 2004.
[36] D. L. McGuinness and F. V. Harmelen. (2004, Feb.). OWL web ontology language overview. [Online]. Available: http://www.w3.org/TR/owl-features/
[37] D. L. McGuinness, R. Fikes, J. Hendler, and L. A. Stein, “DAML+OIL: an ontology language for the semantic web,” IEEE Intelligence Systems, vol. 17, no. 5, pp. 72-80, Sept./Oct. 2002.
[38] S. A. McIlraith, T. C. Son, and H. Zeng, “Semantic web services,” IEEE Intelligent Systems, vol. 16, no. 2, pp. 46-53, March/April 2001.
[39] K. R. McKeown, R. Barzilay, D. Evans, V. Hatzivassiloglou, B. Schiffman, and S. Teufel, “Columbia multi-document summarization: approach and evaluation,” in Proc. of DUC Conference on Text Summarization, USA, 2001.
[40] Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs. Austria: Springer-Verlag, 1996.
[41] R. Navigli and P. Velardi, “Ontology learning and its application to automated terminology translation,” IEEE Intelligent Systems, vol. 18, no. 1, pp. 22-31, Jan./Feb. 2003.
[42] N. F. Noy and D. L. McGuinness. (2001, March). Ontology development 101: a guide to creating your first ontology. [Online]. Available: http://www.ksl.stanford.edu/people/dlm/papers/ontology-tutorial-noy-mcguinness.pdf
[43] S. Park and J. Nang, “Requirements management in large software system development,” in Proc. of IEEE International Conference on Systems, Man and Cybemetics, 1998, pp. 2680-2685.
[44] D. R. Radev, E. Hovy, and K. McKeown, “Introduction to the special issue on summarization,” Computational Linguistics, vol. 28, no. 4, pp. 399-408, Dec. 2002.
[45] H. Saggion and G. Lapalme, “Generating indicative-informative summaries with SumUM,” Computational Linguistics, vol. 28, no. 4, pp. 497-526, 2002.
[46] J. D. Schlesinger, J. M. Conroy, M. E. Okurowski, and D. P. O’Leary, “Machine and human performance for single and multidocument summarization,” IEEE Intelligent Systems, vol. 18, no. 1, pp. 46-54, Jan./Feb. 2003.
[47] V. W. Soo and C. Y. Lin, “Ontology-based information retrieval in a multi-agent system for digital library,” in Proc. of the sixth conference on artificial intelligence and applications, Taiwan, 2001, pp. 241-246.
[48] Y. A. Tijerino and R. Mizoguchi, “MULTIS II: enabling end users to design problem solving engines via two-level task ontologies,” Lecture Notes in Artificial Intelligence 723: Knowledge Acquisition for Knowledge-Based Systems, Caylus, France, 1993, pp. 340-359.
[49] M. Vargas-Vera, E. Motta, J. Domingue, M. Lanzoni, A. Stutt, and F. Ciravegna, “MnM: ontology driven semi-automatic and automatic support for semantic markup,” in Proc. Of the 13th International Conference on Knowledge Engineering and Management (EKAW 2002), Spain, 2002, pp. 379-391.
[50] J. E. L. de Vergara, V. A. Villagrá, and J. Berrocal, “Applying the Web ontology language to management information definitions,” IEEE Communications Magazine, vol. 42, no. 7, pp. 68-74, July 2004.
[51] K. Waikit and M. Lik, “An information theoretic approach for ontology-based interest matching,” in Proc. of the 17th International Conference on Artificial Intelligence IJCAI, Workshop on Ontology Learning, Seattle, Washington, USA, 2001.
[52] R. Watkins and M. Neal, “Why and how of requirements tracing,” IEEE Software, vol. 11, no. 4, pp. 104-106, July 1994.
[53] B. J. Wielinga and A. Th. Schreiber, “Reusable and shareable knowledge bases: a european perspective,” in Proc. of the International Conference on Building and Sharing of Very Large-Scaled Knowledge Bases '93, Tokyo, Japan, Dec, 1993, pp. 103-115.
[54] R. B. Yates and B. R. Neto, Modern Information Retrieval. New York: Addison Wesley, 1999.
[55] J. Y. Yeh, H. R. Ke, W. P. Yang, and I. H. Meng, “Text summarization using a trainable summarizer and latent semantic analysis,” Information Processing and Management, vol. 41, no. 1, pp. 75-95, Jan. 2005.
[56] J. Yen and R. Langari, Fuzzy Logic-Intelligence: Control, and Information. New Jersey: Prentice-Hall, 1999.
[57] S. T. Yuan and J. Sun, “Ontology-based structured consine similarity in document summarization: with applications to mobile audio-based knowledge management,” IEEE Transactions on Systems, Man and Cybernetics Part B, vol. 35, no. 5, pp. 1028-1040, Oct. 2005.
[58] H. J. Zimmermann, Fuzzy Set Theory and Its Applications. Boston: Kluwer Academic Publishers, 1991.
[59] 李允中、王小璠、蘇木春，模糊理論及其應用，台北：全華科技圖書股份有限公司，2003。
[60] 美國卡內基美隆大學軟體工程學院，能力成熟度整合模式 上/下冊，台北：財團法人資訊工業策進會，2002。
[61] 陳雅娟, “基於Ontology之模糊代理人於中文新聞文件摘要技術之研究,” 長榮大學經營管理研究所, 2003.