| 研究生: |
鄧惟玉 Ngoc, Dang Duy |
|---|---|
| 論文名稱: |
使用溝通代理人和關聯擷取來開發學習中文輔助系統 Using Conversation Agent and Extracting Relations to Develop Chinese Learning Supporting System |
| 指導教授: |
朱治平
Chu, Chih-Ping |
| 學位類別: |
碩士 Master |
| 系所名稱: |
電機資訊學院 - 資訊工程學系 Department of Computer Science and Information Engineering |
| 論文出版年: | 2012 |
| 畢業學年度: | 100 |
| 語文別: | 英文 |
| 論文頁數: | 75 |
| 外文關鍵詞: | Chatbot system, Extracting relations, Pattern matching, Learning Chinese Language |
| 相關次數: | 點閱:114 下載:1 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
Nowadays, demand of learning Chinese language is very popular in the world, especially for the Vietnamese students who have been studying in Taiwan. There are many tools and methods used to support Chinese language learning, such as reading textbooks, listening to the tapes or CDs, watching news or movies, etc. But most of them are only one-way interaction that is different from the two-ways interaction in the class room. Learning through a virtual environment using computer is a good way to enhance the performance.
The purpose of this study is to develop a web application system that supports foreign students learning traditional Chinese language. The behavior of this system is the learner inputs a sentence via keyboard and then the system responds a corresponding sentence. Besides, the system can recognize the current learner who is using the system by answering the personal questions like “what is my name?”, “how old am I?”, “how many people are there in my family?”, etc. given by the user.
This system is developed on basis of ALICE (Artificial Linguistic Internet Computer Entity) - an artificial intelligence software which was developed by Dr. Wallace. The operation mechanism of ALICE is pattern matching technique. To reduce quantity of patterns and the occupation of memory, we use a database of “synonym” and “is-a” to convert different sentences with the same meaning into a sentence which matches a specific pattern. In addition, in order to make the computer more friendly and intelligent, we use DIRPE (Dual Iterative Pattern Relation Expansion) - a relations extracting method - to extract the relations that are based on historical conversations between learner and computer. The data extracted will be used for answering the personal questions. This system is implemented in C# language with databases Microsoft SQL server, a AMIL file (a version of XML), and a text file to store data.
1. R. Kurzweil, The Age of Intelligent Machines: Cambridge, MA: MIT Press, 1990.
2. J. Haugland, Artificial Intelligence: The Very Idea: Cambridge, MA: MIT Press, 1985.
3. E. Charniak and D. McDermott, Introduction to Artificial Intelligence: Reading, MA: Addison-Wesley, 1985.
4. R. J. Schalkoff, Artificial Intelligence: An Engineering Approach: New York: McGraw-Hill, 1990.
5. E. Rich and K. Knight, Artificial Intelligence (2nd Edition): New Work: McGraw-Hill, 1991.
6. P. H. Winston, Artificial Intelligence (3rd Edition): Reading, MA: Addison-Wesley, 1992.
7. Bellman, R.E., An Introduction to Artificial Intelligence: Can Computers Think?: San Francisco: Boyd & Fraser, 1978.
8. Wallace, R.S. Alicebot. Available from: http://www.alicebot.org/, 1995.
9. Brin, S., DIRPE-Extracting patterns and relations from the world wide web. WebDB Workshop at 6th International Conference on Extending Database Technology, EDBT. 1998.
10. Government, T., Speak Mandarin in one thousand words, http://edu.ocac.gov.tw/interact/ebook/1000_w2/index_classList_0.html.
11. NCKU, Practice audio - visual Chinese 2nd edition, Vol1 & Vol2, Cheng Kung Book Co., LTD.
12. S. J. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, second edition: Prentice Hall, 2003.
13. G. F. Luger and W. A. Stubblefield, Artificial Intelligence: Structures and Strategies for Complex Problem Solving (2nd Edition): Redwood City, CA: Benjamin/Cummings, 1993.
14. J. Weizenbaum, ELIZA-a computer program for the study of natural language communication between man and machine. Communications of the ACM, vol. 9, pp. 36-45, 1966.
15. The Loebner Prize. Available from: http://www.loebner.net/Prizef/loebner-prize.html.
16. Wallace, R.S. AIML Overview. Available from: http://www.pandorabots.com/pandora/pics/wallaceaimltutorial.html.
17. Wallace, R.S., The Anatomy of A.L.I.C.E. 2004. in A.L.I.C.E Artificial Intelligence Foundation, Inc, 2004.
18. Ringate, T. AIML Primer. Available from: http://www.alicebot.org/documentation/aiml-primer.html, Last update October 30, 2011.
19. R. S. Wallace. AIML Pattern Matching Simplified. Available from: http://www.alicebot.org/documentation/matching.html, updated 20 October 2007.
20. Simmons, R.F., Natural Language Question - Answering Systems, 1969.
21. Question and answering system. Available from: http://en.wikipedia.org/wiki/Question_answering.
22. D. Roth, C.C., X. Li, P. Morie, R. Nagarajan, N. Rizzolo, K. Small, W. Yih, Question-Answering via Enhanced Understanding of Questions. Proceedings of the 11th Text Retrieval Conference (TREC), 2002.
23. E. Hovy, L.G., U. Hermjakob, M. Junk, and C-Y Lin, Question Answering in Webclopedia. Proceedings of the TREC-9 Conference. NIST, Gaithersbur MD, 2000.
24. Deepak Ravichandran, E.H., Learning Surface Text Patterns for a Question Answering System. In Proceedings of the ACL Conference, 2002, Information Sciences Institute University of Southern California, 2000.
25. John Burger, C.C., Vinay Chaudhri, Robert Gaizauskas, Sanda Harabagiu, David Israel, Christian Jacquemin, Chin-Yew Lin, Steve Maiorano, George Miller, Dan Moldovan, Bill Ogden, John Prager, Ellen Riloff, Amit Singhal, Rohini Shrihari, Tomek Str, Tomek Strzalkowski, Ellen Voorhees, Ralph Weishedel Issues, Tasks and Program Structures to Roadmap Research in Question & Answering (Q&A).
26. H.Tollervey, N., http://www.ntoll.org/.