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題名 英文文法關係之型態探勘
Pattern Mining on English Grammatical Relations
作者 蔡吉章
Tsai, Chi Chang
貢獻者 劉吉軒
Liu, Jyi Shane
蔡吉章
Tsai, Chi Chang
關鍵詞 關聯法則
文法樣式
文法關係
Association rule
Grammatical patterns
Grammatical relations
LSA
日期 2009
上傳時間 9-May-2016 12:02:34 (UTC+8)
摘要 一些研究發現常見的ESL(English as a Second Language)學習者在英語寫作時的錯誤為:用字不適當、動詞的形式不正確、句子缺少主詞、以及動詞時態錯誤。這些錯誤主要是起因於:字彙之不足、不清楚文法概念、本身母語的干擾。為了改善ESL學習者的寫作。我們希望能從文法關係的資訊來提供協助。目前,研究文法關係大多著重於字詞構成的單一文法關係,然而字詞在句中可能同時具備了不只一種文法關係。在我們的研究中,我們先發展文法關係樣式辨識系統。從句子中利用此系統提供使用者可搭配的文法關係,以了解可供使用的對應字詞。對應字詞可以輔助學習者適當地使用此關鍵字。此外設計使用者介面供查詢文法關係。以上,我們利用文法關係與搭配字詞來提供使用者英語寫作上的協助。而找尋樣式的做法,我們提出關聯法則和LSA(Latent Semantic Analysis)來實作。
Some study found some common ESL (English as a Second Language) learners English Writing Error: improper use of the word, the verb form is not correct, the sentence lack of subject and verb tense errors. These errors are mainly due to: lack of vocabulary, grammar concept is not clear, the mother-tongue interference. In order to improve the ESL writing, we hope that the information from the grammatical relation to provide assistance. At present, the studies of grammatical relation mostly emphasize the word consisting of a single grammatical relation. However, words in the sentence may also have more than one grammatical relation. In our study, we first develop grammatical relation pattern recognition system. From the sentence using the system provides users with the grammatical relation, in order to understand the availability of the corresponding words. The corresponding words can help learners make appropriate use of this keyword. In addition the design of the user interface provides querying grammatical relation. This work makes use of grammatical relation and collocation in order to provide users with the assistance of English writing. And look for patterns of practice, we have proposed association rules and LSA (Latent Semantic Analysis) to implement.
第一章 緒論- 1 -
     1.1簡介- 1 -
     1.2動機和目的- 2 -
     1.3預期成果與貢獻- 5 -
     第二章 文獻探討- 7 -
     2.1背景研究- 7 -
     2.2語料庫(CORPUS)- 8 -
     2.3詞性標註(PART OF SPEECH TAGGING/POS TAGGING)- 9 -
     2.4語彙索引(CONCORDANCE)- 12 -
     2.5字詞的搭配(COLLOCATION)和文法關係(GRAMMATICAL RELATIONS)- 14 -
     2.6樣式(PATTERN)- 17 -
     2.7 WORD SKETCH、SKETCH ENGINE- 18 -
     2.8 TANGO- 19 -
     2.9 YOURDICTIONARY- 21 -
     2.10 小結- 21 -
     第三章 研究方法- 23 -
     3.1 英文樣式尋找方法- 23 -
     3.2 系統模組- 25 -
     3.2.1 文法模組- 25 -
     3.2.2 辨識模組- 29 -
     3.2.2.1 辨識模組a:使用關聯法則- 29 -
     3.2.2.2 辨識模組b:使用LSA- 30 -
     3.2.3 查詢模組- 36 -
     3.3 小結- 37 -
     第四章 實驗分析設計- 38 -
     4.1 實驗資料- 38 -
     4.2 實驗評估- 55 -
     4.3 實驗結果分析- 66 -
     4.3.1文法關係分析- 66 -
     4.3.2 字詞關係分析- 68 -
     4.4 總結- 77 -
     第五章 結論與未來方向- 79 -
     5.1 結論- 79 -
     5.2 未來研究方向- 80 -
     參考文獻- 81 -
     附錄- 84 -
     A-1-SE中的單字及其文法關係- 84 -
     A-1-YD中的單字及其文法關係- 99 -
     A-1-LSA中的單字及其文法關係- 106 -
     A-1-AR中的單字及其文法關係- 136 -
     B-1 SKETCH ENGINE對應在LSA和AR的範圍- 151 -
     B-2 YOURDICTIONARY對應在LSA和AR的範圍- 152 -
參考文獻 [1] Greene, B. B. and G. M. Rubin (1971). Automatic grammatical tagging of English. Dept. of Linguistics, Brown University.
     [2] http://www.ucl.ac.uk/english-usage/ice/ International Corpus of English.
     [3] Garside, R. (1987). The CLAWS word-tagging system. The Computational Analysis of English. Longman, London: 30-41.
     [4] Tseng, C. Y. and A. Caticha (2004). Maximum entropy and the variational method in statistical mechanics: an application to simple fluids. In the process of reviewing for publication in Phys. Rev. E.
     [5] Hunston, S. and G. Francis (2000) Pattern grammar: a corpus-driven approach to the lexical grammar of English. Computational Linguistics 27(2).
     [6] http://www.collins.co.uk/corpus/CorpusSearch.aspx Cobuild Concordance and Collocations Sampler.
     [7] Kilgarriff, A. and D. Tugwell (2001). WORD SKETCH: Extraction and Display of Significant Collocations for Lexicography.
     [8] Benson, M., E. Benson, et al. (1997). The BBI dictionary of English word combinations (Revised Edition). Amsterdam & Philadelphia: John Benjamins Publis.
     [9] McEnery, T. and A. Wilson (2001). Corpus Linguistics, Edinburgh University Press.
     [10] Moehkardi, R. R. D. (2002). Grammatical and lexical English collocations: some possible problems to Indonesian learners of English. Humaniora 14(1).
     [11] Toutanova, K., D. Klein, et al. (2003). Feature-rich part-of-speech tagging with a cyclic dependency network. Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology-Volume 1: 173-180.
     [12] Sinclair, J. (1995). Collins Cobuild English dictionary, HarperCollins.
     [13] http://www.sketchengine.co.uk/ Sketch Engine
     [14] http://nlp.stanford.edu/downloads/lex-parser.shtml Stanford Parser
     [15] Klein, D. and C. D. Manning (2003). Fast exact inference with a factored model for natural language parsing. Advances in Neural Information Processing Systems 15: Proceedings of the 2002 Conference.
     [16] Klein, D. and C. D. Manning (2003). Accurate unlexicalized parsing. Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics: 423-430.
     [17] Crochemore, M. and W. Rytter (2002). Jewels of Stringology, World Scientific.
     [18] http://tw.dictionary.yahoo.com/ Yahoo字典
     [19] http://www.dreye.com/tw/ Dr.eye譯典通
     [20] http://www.eslpod.com/website/index.php ESL Podcast
     [21] http://wordnet.princeton.edu/ WordNet
     [22] Jian, J. Y., Y. C. Chang, et al. (2004). TANGO: bilingual collocational concordancer. Proceedings of the ACL 2004 on Interactive poster and demonstration sessions.
     [23] http://www.natcorp.ox.ac.uk/ British National Corpus
     [24] Agrawal, R. and R. Srikant (1994). Fast algorithms for mining association rules. In Proc. 1994 Int. Conf. Very Large Data Bases (VLDB`94), Santiago, Chile, pp. 487-499.
     [25] Choueka, Y. (1988). Looking for needles in a haystack. In Proceedings, RIAO Conference on User-Oriented Context Based Text and Image Handling, 609-623.
     [26] Church, K. W. and P. Hanks (1990). Word association norms, mutual information, and lexicography. Computational Linguistics 16(1): 22-29.
     [27] Smadja, F. (1993). Retrieving collocations from text: Xtract. Computational Linguistics 19(1): 143-177.
     [28] http://www.gept.org.tw/# 財團法人語言訓練測驗中心
     [29] Chuang, T. C., J. Y. Jian, et al. (2005). Collocational translation memory extraction based on statistical and linguistic information. 中文計算語言學期刊 10(3): 329-345.
     [30] de Marneffe, M. C., B. MacCartney, et al. (2006). Generating typed dependency parses from phrase structure parses. In Proceedings of 5th International Conference on Language Resources and Evaluation(LREC2006).
     [31] Levy, R. and G. Andrew (2006). Tregex and Tsurgeon: tools for querying and manipulating tree data structures. In Proceedings of 5th International Conference on Language Resources and Evaluation(LREC2006).
     [32] Landauer, T. K., P. W. Foltz, et al. (1998). An introduction to latent semantic analysis. Discourse Processes 25(2-3): 259-284.
     [33] http://www.yourdictionary.com/ YourDictionary
     [34] Tan, Hui-mien. A Study of EFL Learners` Writing Errors and Instructional Strategies. Center for General Education, Kun Shan University.
     [35] Agrawal, R., T. Imieli?ski, et al. (1993). Mining association rules between sets of items in large databases, Proceedings of ACM SIGMOD, 207-216.
描述 碩士
國立政治大學
資訊科學學系
95753037
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0095753037
資料類型 thesis
dc.contributor.advisor 劉吉軒zh_TW
dc.contributor.advisor Liu, Jyi Shaneen_US
dc.contributor.author (Authors) 蔡吉章zh_TW
dc.contributor.author (Authors) Tsai, Chi Changen_US
dc.creator (作者) 蔡吉章zh_TW
dc.creator (作者) Tsai, Chi Changen_US
dc.date (日期) 2009en_US
dc.date.accessioned 9-May-2016 12:02:34 (UTC+8)-
dc.date.available 9-May-2016 12:02:34 (UTC+8)-
dc.date.issued (上傳時間) 9-May-2016 12:02:34 (UTC+8)-
dc.identifier (Other Identifiers) G0095753037en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/94860-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學學系zh_TW
dc.description (描述) 95753037zh_TW
dc.description.abstract (摘要) 一些研究發現常見的ESL(English as a Second Language)學習者在英語寫作時的錯誤為:用字不適當、動詞的形式不正確、句子缺少主詞、以及動詞時態錯誤。這些錯誤主要是起因於:字彙之不足、不清楚文法概念、本身母語的干擾。為了改善ESL學習者的寫作。我們希望能從文法關係的資訊來提供協助。目前,研究文法關係大多著重於字詞構成的單一文法關係,然而字詞在句中可能同時具備了不只一種文法關係。在我們的研究中,我們先發展文法關係樣式辨識系統。從句子中利用此系統提供使用者可搭配的文法關係,以了解可供使用的對應字詞。對應字詞可以輔助學習者適當地使用此關鍵字。此外設計使用者介面供查詢文法關係。以上,我們利用文法關係與搭配字詞來提供使用者英語寫作上的協助。而找尋樣式的做法,我們提出關聯法則和LSA(Latent Semantic Analysis)來實作。zh_TW
dc.description.abstract (摘要) Some study found some common ESL (English as a Second Language) learners English Writing Error: improper use of the word, the verb form is not correct, the sentence lack of subject and verb tense errors. These errors are mainly due to: lack of vocabulary, grammar concept is not clear, the mother-tongue interference. In order to improve the ESL writing, we hope that the information from the grammatical relation to provide assistance. At present, the studies of grammatical relation mostly emphasize the word consisting of a single grammatical relation. However, words in the sentence may also have more than one grammatical relation. In our study, we first develop grammatical relation pattern recognition system. From the sentence using the system provides users with the grammatical relation, in order to understand the availability of the corresponding words. The corresponding words can help learners make appropriate use of this keyword. In addition the design of the user interface provides querying grammatical relation. This work makes use of grammatical relation and collocation in order to provide users with the assistance of English writing. And look for patterns of practice, we have proposed association rules and LSA (Latent Semantic Analysis) to implement.en_US
dc.description.abstract (摘要) 第一章 緒論- 1 -
     1.1簡介- 1 -
     1.2動機和目的- 2 -
     1.3預期成果與貢獻- 5 -
     第二章 文獻探討- 7 -
     2.1背景研究- 7 -
     2.2語料庫(CORPUS)- 8 -
     2.3詞性標註(PART OF SPEECH TAGGING/POS TAGGING)- 9 -
     2.4語彙索引(CONCORDANCE)- 12 -
     2.5字詞的搭配(COLLOCATION)和文法關係(GRAMMATICAL RELATIONS)- 14 -
     2.6樣式(PATTERN)- 17 -
     2.7 WORD SKETCH、SKETCH ENGINE- 18 -
     2.8 TANGO- 19 -
     2.9 YOURDICTIONARY- 21 -
     2.10 小結- 21 -
     第三章 研究方法- 23 -
     3.1 英文樣式尋找方法- 23 -
     3.2 系統模組- 25 -
     3.2.1 文法模組- 25 -
     3.2.2 辨識模組- 29 -
     3.2.2.1 辨識模組a:使用關聯法則- 29 -
     3.2.2.2 辨識模組b:使用LSA- 30 -
     3.2.3 查詢模組- 36 -
     3.3 小結- 37 -
     第四章 實驗分析設計- 38 -
     4.1 實驗資料- 38 -
     4.2 實驗評估- 55 -
     4.3 實驗結果分析- 66 -
     4.3.1文法關係分析- 66 -
     4.3.2 字詞關係分析- 68 -
     4.4 總結- 77 -
     第五章 結論與未來方向- 79 -
     5.1 結論- 79 -
     5.2 未來研究方向- 80 -
     參考文獻- 81 -
     附錄- 84 -
     A-1-SE中的單字及其文法關係- 84 -
     A-1-YD中的單字及其文法關係- 99 -
     A-1-LSA中的單字及其文法關係- 106 -
     A-1-AR中的單字及其文法關係- 136 -
     B-1 SKETCH ENGINE對應在LSA和AR的範圍- 151 -
     B-2 YOURDICTIONARY對應在LSA和AR的範圍- 152 -
-
dc.description.tableofcontents 第一章 緒論- 1 -
     1.1簡介- 1 -
     1.2動機和目的- 2 -
     1.3預期成果與貢獻- 5 -
     第二章 文獻探討- 7 -
     2.1背景研究- 7 -
     2.2語料庫(CORPUS)- 8 -
     2.3詞性標註(PART OF SPEECH TAGGING/POS TAGGING)- 9 -
     2.4語彙索引(CONCORDANCE)- 12 -
     2.5字詞的搭配(COLLOCATION)和文法關係(GRAMMATICAL RELATIONS)- 14 -
     2.6樣式(PATTERN)- 17 -
     2.7 WORD SKETCH、SKETCH ENGINE- 18 -
     2.8 TANGO- 19 -
     2.9 YOURDICTIONARY- 21 -
     2.10 小結- 21 -
     第三章 研究方法- 23 -
     3.1 英文樣式尋找方法- 23 -
     3.2 系統模組- 25 -
     3.2.1 文法模組- 25 -
     3.2.2 辨識模組- 29 -
     3.2.2.1 辨識模組a:使用關聯法則- 29 -
     3.2.2.2 辨識模組b:使用LSA- 30 -
     3.2.3 查詢模組- 36 -
     3.3 小結- 37 -
     第四章 實驗分析設計- 38 -
     4.1 實驗資料- 38 -
     4.2 實驗評估- 55 -
     4.3 實驗結果分析- 66 -
     4.3.1文法關係分析- 66 -
     4.3.2 字詞關係分析- 68 -
     4.4 總結- 77 -
     第五章 結論與未來方向- 79 -
     5.1 結論- 79 -
     5.2 未來研究方向- 80 -
     參考文獻- 81 -
     附錄- 84 -
     A-1-SE中的單字及其文法關係- 84 -
     A-1-YD中的單字及其文法關係- 99 -
     A-1-LSA中的單字及其文法關係- 106 -
     A-1-AR中的單字及其文法關係- 136 -
     B-1 SKETCH ENGINE對應在LSA和AR的範圍- 151 -
     B-2 YOURDICTIONARY對應在LSA和AR的範圍- 152 -
zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0095753037en_US
dc.subject (關鍵詞) 關聯法則zh_TW
dc.subject (關鍵詞) 文法樣式zh_TW
dc.subject (關鍵詞) 文法關係zh_TW
dc.subject (關鍵詞) Association ruleen_US
dc.subject (關鍵詞) Grammatical patternsen_US
dc.subject (關鍵詞) Grammatical relationsen_US
dc.subject (關鍵詞) LSAen_US
dc.title (題名) 英文文法關係之型態探勘zh_TW
dc.title (題名) Pattern Mining on English Grammatical Relationsen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) [1] Greene, B. B. and G. M. Rubin (1971). Automatic grammatical tagging of English. Dept. of Linguistics, Brown University.
     [2] http://www.ucl.ac.uk/english-usage/ice/ International Corpus of English.
     [3] Garside, R. (1987). The CLAWS word-tagging system. The Computational Analysis of English. Longman, London: 30-41.
     [4] Tseng, C. Y. and A. Caticha (2004). Maximum entropy and the variational method in statistical mechanics: an application to simple fluids. In the process of reviewing for publication in Phys. Rev. E.
     [5] Hunston, S. and G. Francis (2000) Pattern grammar: a corpus-driven approach to the lexical grammar of English. Computational Linguistics 27(2).
     [6] http://www.collins.co.uk/corpus/CorpusSearch.aspx Cobuild Concordance and Collocations Sampler.
     [7] Kilgarriff, A. and D. Tugwell (2001). WORD SKETCH: Extraction and Display of Significant Collocations for Lexicography.
     [8] Benson, M., E. Benson, et al. (1997). The BBI dictionary of English word combinations (Revised Edition). Amsterdam & Philadelphia: John Benjamins Publis.
     [9] McEnery, T. and A. Wilson (2001). Corpus Linguistics, Edinburgh University Press.
     [10] Moehkardi, R. R. D. (2002). Grammatical and lexical English collocations: some possible problems to Indonesian learners of English. Humaniora 14(1).
     [11] Toutanova, K., D. Klein, et al. (2003). Feature-rich part-of-speech tagging with a cyclic dependency network. Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology-Volume 1: 173-180.
     [12] Sinclair, J. (1995). Collins Cobuild English dictionary, HarperCollins.
     [13] http://www.sketchengine.co.uk/ Sketch Engine
     [14] http://nlp.stanford.edu/downloads/lex-parser.shtml Stanford Parser
     [15] Klein, D. and C. D. Manning (2003). Fast exact inference with a factored model for natural language parsing. Advances in Neural Information Processing Systems 15: Proceedings of the 2002 Conference.
     [16] Klein, D. and C. D. Manning (2003). Accurate unlexicalized parsing. Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics: 423-430.
     [17] Crochemore, M. and W. Rytter (2002). Jewels of Stringology, World Scientific.
     [18] http://tw.dictionary.yahoo.com/ Yahoo字典
     [19] http://www.dreye.com/tw/ Dr.eye譯典通
     [20] http://www.eslpod.com/website/index.php ESL Podcast
     [21] http://wordnet.princeton.edu/ WordNet
     [22] Jian, J. Y., Y. C. Chang, et al. (2004). TANGO: bilingual collocational concordancer. Proceedings of the ACL 2004 on Interactive poster and demonstration sessions.
     [23] http://www.natcorp.ox.ac.uk/ British National Corpus
     [24] Agrawal, R. and R. Srikant (1994). Fast algorithms for mining association rules. In Proc. 1994 Int. Conf. Very Large Data Bases (VLDB`94), Santiago, Chile, pp. 487-499.
     [25] Choueka, Y. (1988). Looking for needles in a haystack. In Proceedings, RIAO Conference on User-Oriented Context Based Text and Image Handling, 609-623.
     [26] Church, K. W. and P. Hanks (1990). Word association norms, mutual information, and lexicography. Computational Linguistics 16(1): 22-29.
     [27] Smadja, F. (1993). Retrieving collocations from text: Xtract. Computational Linguistics 19(1): 143-177.
     [28] http://www.gept.org.tw/# 財團法人語言訓練測驗中心
     [29] Chuang, T. C., J. Y. Jian, et al. (2005). Collocational translation memory extraction based on statistical and linguistic information. 中文計算語言學期刊 10(3): 329-345.
     [30] de Marneffe, M. C., B. MacCartney, et al. (2006). Generating typed dependency parses from phrase structure parses. In Proceedings of 5th International Conference on Language Resources and Evaluation(LREC2006).
     [31] Levy, R. and G. Andrew (2006). Tregex and Tsurgeon: tools for querying and manipulating tree data structures. In Proceedings of 5th International Conference on Language Resources and Evaluation(LREC2006).
     [32] Landauer, T. K., P. W. Foltz, et al. (1998). An introduction to latent semantic analysis. Discourse Processes 25(2-3): 259-284.
     [33] http://www.yourdictionary.com/ YourDictionary
     [34] Tan, Hui-mien. A Study of EFL Learners` Writing Errors and Instructional Strategies. Center for General Education, Kun Shan University.
     [35] Agrawal, R., T. Imieli?ski, et al. (1993). Mining association rules between sets of items in large databases, Proceedings of ACM SIGMOD, 207-216.
zh_TW