| 摘要(英) |
Chinese is a difficult language to learn, because of Chinese is not alphabetic writing it is very hard to know the pronunciation of each word. So we hope to design a more convenient way of learning for the Chinese beginners and provide to officers on the edition of teaching materials. Therefore we require a lot of Chinese characters, so we choose to use part of the "Chinese Character Component Searching System of Academia Sinica" has the form of phonetic sound of the pictophonetic characters. Chinese beginners can determine from phonetic complement to the pronunciation of a word, because of pictophonetic characters are accounted for more than 90 percent of Chinese characters that are general used and formed by phonetic complement and semantic complement. Check all the words’ different Pronunciation through "Hanyu Da Cidian", and then marked by the experts in the literature and confirm the phonetic complement. Afterwards to use multilevel association rule mining to mine the rules of pictophonetic characters to words. Users can choose specified level to observe the effect of not only the pronunciation level, but also initials, vowels, tones level and phonemes level. Final we can suggest some words to the beginners.
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| 參考文獻 |
[1] Shen X., “Origin of Chinese Character,”100. (說文解字.敘 , 許慎)
[2] http://cdp.sinica.edu.tw/cdphanzi/ , Chinese Character Component Searching System of Academia Sinica.
[3] Hanyu da zidian weiyuanhui 漢語大字典委員會, Hanyu da zidian 漢語大字典 ("Comprehensive Chinese Character Dictionary"), 8 vols., Hubei cishu chubanshe and Sichuan cishu chubanshe, 1986-1989.
[4] Agrawal R.and Srikant R., "Fast algorithm for mining association rules, " by Proc. of 1994 Int. Conf.on Very Large Data Bases (VLDB'94), pages 487-499, Santiago, Chile, Sept. 1994.
[5] Klemettinen M., Mannila H., Ronkainen P., Toivonen H., and Verkamo I., "Finding interesting rules from large sets of discovered association rules, " by Proc. 3rd Int. Conf. Information and Knowledge Management (CIKM'94), pages 401-408, Gaithersburg, MD, Nov. 1994.
[6] Han J., Pei J., and Yin Y., "Mining frequent patterns without candidate generation, “ by Proc. 2000 ACM-SIGMOD Int. Conf. Management of Data (SIGMOD'00), pages 1-12, Dallas, TX, May 2000.
[7] Meng-Feng Tsai and Yi-Ming Lee, "Mining Self-derivable Multilevel FP-tree From a Transactional Database", National Central University, Taiwan, Master Thesis, 2006.
[8] Jiawei H., Yongjian F., "Discovery of Multiple-Level Association Rules from Large Databases, " by Proc. of 1995 Int'l Conf. on Very Large Data Bases (VLDB'95).
[9] Jiawei H. and Micheline K., Data Mining: Concepts and Techniques, 2nd ed. pages 228-231, Morgan Kaufmann Publishers, March 2006.
[10] http://140.115.52.39/chinaweb/rule.html
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