近十年網路的發明帶動著資訊大量的流通。許多知識已經數位化，在資訊氾濫的今日，如何正確、有效率的重複利用知識是大家所感興趣地。目前最常被用來尋找知識的工具是Google或Yahoo搜尋引擎，所依賴是輸入關鍵字利用IR (Information Retrieval)的技術獲取網頁相關資訊，再由使用者自行閱讀並組織知識。如果搜尋結果的資料非常龐大，使用者必須花費很多時間去瀏覽內容。
問答系統(Question Answering system, QA system) 則是利用使用者所輸入的問句，依據語意提供最適切的答案。不但節省使用者大量閱讀資料的時間，也達到知識的組織與再利用。然而問答系統的困難在於問題語意的分析與知識的萃取，如果無法正確擷取語意，系統將無法正確回答問題。
本篇論文是探討自動化建構部份體育知識本體(Ontology)的方法提供問答系統的語意搜尋資料來源。其方法是將問句本身的語意擴展，再從體育新聞內容自動建構所屬的部份知識本體，作為回覆答案的資料集。經過實測所得數據顯示本論文方法有顯著的效果。

With the development of World Wide Web (WWW), huge amounts of data are exchanged on the Internet. How to reuse knowledge correctly, effectively and conveniently is an important issue. Nowadays, the most popular tools for seeking the knowledge in network are Google or Yahoo keyword-based search engine. After obtaining the documents of webpage which gained from search engine, users have to read and organize it themselves. If the information you obtained was extremely huge, it may take too much time to organize it easily.
The question answering system (QA system) provides the most appropriate answer for user by giving a question. It not only save the time but also organize and reuse knowledge for users. However, it is difficult for QA system to understand the language semantic and to extract knowledge from question and source documents. In this thesis, we design the dynamically automatic ontology constructor for semantic search. For answering user question, we construct partial sports ontology by expanding the semantic of question. After the ontology is built, the system can infer the answer without asking users to read the whole document sets. NBA and CPBL sport news pages are used as source documents in our research, while the approach can be used in other domain.

[1] B. A. Davey and H. A. Priestley, Introduction to Lattices and Order: Cambridge University Press, 2002.
[2] Bill Swartout, Ramesh Patil, Kevin Knight, Tom Russ, Kevin Knight, and Tom Russ, "Toward Distributed Use of Large-Scale Ontologies," in Symposium on Ontological Engineering of AAAI Stanford, California, 1997.
[3] Frank Buchli, "Detecting Software Patterns using Formal Concept Analysis," in der Philosophisch-naturwissenschaftlichen Fakult‥: University of Bern, 2003.
[4] Cheng-Wei Shih Cheng-Wei Lee, Min-Yuh Day, Tzong-Han Tsai, Tian-Jian Jiang, Chia-Wei Wu, Cheng-Lung Sung, Yu-Ren Chen, Shih-Hung Wu and Wen-Lian Hsu, "ASQA: Academia Sinica Question Answering System for NTCIR-5 CLQA," in Proceedings of NTCIR-5 Workshop, Tokyo, Japan, 2005, pp. 202-208.
[5] CKIP中文詞知識庫小組, http://rocling.iis.sinica.edu.tw/CKIP/index.htm.
[6] Patrick du Boucher-Ryan and Derek Bridge, "Collaborative Recommending using Formal Concept Analysis," Knowledge-Based Systems, vol. 19, pp. 309-315, 2006.
[7] D. Fensel, F. van Harmelen, I. Horrocks, D. L. McGuinness, and P. F. Patel-Schneider, "OIL: an ontology infrastructure for the Semantic Web," Intelligent Systems, vol. 16, pp. 38-45, 2001.
[8] Dieter Fensel, Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce, Second Edition ed.: Springer, 2004.
[9] Anna Formica, "Ontology-based concept similarity in Formal Concept Analysis," Information Sciences, vol. 176, pp. 2624-2641, 2006.
[10] Google, http://www.google.com/intl/zh-TW/why_use.html.
[11] Chinese Knowledge Information Processing Group, "CKIP AutoTag," Academic sinica, 1998.
[12] T. R. Gruber, "A TRANSLATION APPROACH TO PORTABLE ONTOLOGY SPECIFICATIONS," Knowledge Acquisition, vol. 5, pp. 199-220, Jun 1993.
[13] Kuang-hua Chen Hsin-Hsi Chen, "Overview of CLQA Task at the Fifth NTCIR Workshop," in Proceedings of NTCIR-5 Workshop Meeting, December 6-9, 2005, Tokyo, Japan, 2005, pp. 175-185.
[14] Chen Kuang-hua and Chen Hsin-Hsi, "Cross-Language Chinese Text Retrieval in NTCIR Workshop: towards Cross-Language multilingual Text Retrieval," SIGIR Forum, vol. 35, pp. 12-19, 2001.
[15] Tung-Ho Wu Lun-Wei Ku, Li-Ying Lee and Hsin-Hsi Chen, "Construction of an Evaluation Corpus for Opinion Extraction," in Proceedings of NTCIR-5 Workshop Meeting, December 6-9, 2005, Tokyo, Japan, 2005, pp. 513-520.
[16] Siff Michael and W. Reps Thomas, "Identifying modules via concept analysis," in Proceedings of the International Conference on Software Maintenance: IEEE Computer Society, 1997.
[17] R. Neches, R. Fikes, T. Finin, T. Gruber, R. Patil, T. Senator, and W. R. Swartout, "ENABLING TECHNOLOGY FOR KNOWLEDGE SHARING," Ai Magazine, vol. 12, pp. 36-56, Fal 1991.
[18] Natalya F. Noy and Deborah L. McGuinness, "Ontology Development 101: A Guide to Creating Your First Ontology," Stanford Medical Informatics Technical Report SMI-2001-0880, March 2001. 2001.
[19] Hyo-Jung Oh, Sung Hyon Myaeng, and Myung-Gil Jang, "Semantic passage segmentation based on sentence topics for question answering," Information Sciences, vol. 177, pp. 3696-3717, 2007.
[20] udn.com, http://udn.com/.
[21] Ellen M. Voorhees, "Overview of the TREC 2001 Question Answering Track," in Proceedings of the Tenth Text REtreival Conference (TREC 2001), 2002, pp. 42-51.
[22] Ellen M. Voorhees, "Overview of the TREC 2003 Question Answering Track," in Proceedings of the Twelfth Text REtrieval Conference (TREC 2003), 2004, pp. 54-68.
[23] Ellen M. Voorhees, "Overview of the TREC 2004 Question Answering Track," in Proceedings of the Thirteenth Text REtrieval Conference (TREC 2004), 2005, pp. 52-62.
[24] Keh-Jiann Chen Wei-Yun Ma, "A bottom-up Merging Algorithm for Chinese Unknown Word Extraction," in Proceedings of ACL workshop on Chinese Language Processing 2003, pp. 31-38.
[25] Sung-Shun Weng, Hsine-Jen Tsai, Shang-Chia Liu, and Cheng-Hsin Hsu, "Ontology construction for information classification," Expert Systems with Applications, vol. 31, pp. 1-12, 2006.
[26] CPBL 中華職棒大聯盟, http://www.cpbl.com.tw/.