跳到主要內容

臺灣博碩士論文加值系統

(44.212.99.248) 您好!臺灣時間:2023/01/28 12:43
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:黃瀚萱
研究生(外文):Hen-Hsen Huang
論文名稱:中文語篇標記解釋與語篇關係辨識及其在意見極性分析之研究
論文名稱(外文):Interpretation of Chinese Discourse Markers, Discourse Relation Recognition, and their Relationships with Sentiment Polarity
指導教授:陳信希陳信希引用關係
指導教授(外文):Hsin-Hsi Chen
口試委員:張俊盛吳宗憲曾元顯陳光華張嘉惠鄭卜壬古倫維
口試委員(外文):Jason S. ChangChung-Hsien WuYuen-Hsien TsengKuang-Hua ChenChia-Hui ChangPu-Jen ChengLun-Wei Ku
口試日期:2014-07-25
學位類別:博士
校院名稱:國立臺灣大學
系所名稱:資訊工程學研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2014
畢業學年度:102
語文別:英文
論文頁數:102
中文關鍵詞:自然語言處理中文語篇分析語篇關係辨識語篇標記意見極性
外文關鍵詞:Natural Language ProcessingChinese Discourse AnalysisDiscourse Relation RecognitionDiscourse MarkerSentiment Polarity
相關次數:
  • 被引用被引用:0
  • 點閱點閱:571
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:1
語篇關係是語篇單元(如子句、句子、或句群)之間的修辭關係,常見的語篇關係有時序、因果、轉折、推展等。語篇關係呈現了文句承接的邏輯,影響文意的表達和解讀。利用電腦自動偵測語篇關係,是新興的研究領域。隨著Rhetoric Structure Theory Discourse Treebank (RST-DT) 與Penn Discourse Treebank (PDTB) 等語料資源釋出,英文的語篇關係分析已經有了一些成果,進而應用到自動摘要、意見分析、文本蘊涵、事件辨識等領域。反觀中文,由於語料資源的缺乏,以及中文本身的複雜性,使得中文語篇關係的研究更具挑戰性。
本篇論文對於中文語篇關係識別、中文語篇標記、語篇關係與意見極性的關聯性,做了全面性的探討。我們發展了一套學習模型,可以識別句內及句間等兩種層次的語篇關係,同時也觸及語篇剖析的問題。語篇剖析可以將語篇單元之間的上下階層以及指涉範圍,解析成樹狀結構,從複雜的語句中挖掘出更多資訊。特別是中文的長句,超過三四個子句,沒有語篇結構的資訊,則不易解釋整個句子的意涵。對此,我們發展了初步的統計學習的模型,對中文句子進行句內的語篇剖析。
在語篇關係識別與剖析的實驗過程中,我們發現語篇標記(一些具有語篇資訊的連接詞等詞彙,例如「因為」、「但是」)是語篇關係識別的重要線索。但在中文裡,語篇標記常有一字多義的歧義性,連帶干擾識別模型的效能。我們運用鉅量資料,配合半監督式機器學習法來探索歧義性的問題,評估每個語篇標記對於四大類語篇關係的分佈情況。從資料中習得的分佈資訊,作為語篇關係識別的特徵線索,效果比使用專家制定的詞典更好。
我們也探討了語篇關係與意見極性之間的關聯。像「轉折」關係,它的兩個語篇單元常常形成對立的意見極性,較常用於呈現負面意見。相對的,「時序」和「推展」所陳述的內容,則較為中立,較少涉及情緒表態。由於語篇關係與意見極性此之間的密切關聯,語篇關係識別的結果可以作為線索,應用於意見分析。
在本論文中,我們所處理的語篇關係是最基本的「時序」、「因果」、「轉折」、「推展」等四大類型。未來我們希望可以探討更細緻的語篇關係,並且進一步處理句內、句間、句群等不同層次的語篇剖析。

Discourse relation is the rhetorical relation between two discourse units (i.e. clauses, sentences, or blocks of sentences). The famous discourse relations include Temporal, Contingency, Comparison, Expansion, and so on. A discourse relation indicates how its two discourse units cohere, and this information influences the meaning of text. Discourse relation is important clue to many applications such as summarization, opinion mining, textual entailment, and event recognition.
Recently the research on automatically English discourse relation recognition is rapid growth due to the release of corpora like Rhetoric Structure Theory Discourse Treebank (RST-DT) and Penn Discourse Treebank (PDTB). Unlike English, Chinese discourse relation recognition is more challenging because of the lack of resources and the special issues in Chinese.
In this dissertation, we give an in-depth study on Chinese discourse relation analysis. We propose a statistical algorithm to recognize the discourse relation in both levels of inter-sentential and intra-sentential. We also show our preliminary results on Chinese discourse parsing at sentence level. In Chinese, many long sentences contain more than two clauses and form complex discourse structures. Discourse parsing fetches the hierarchical structure and relation among the clauses in a given sentence.
Discourse markers are key clue to discourse process, but the use of Chinese discourse marker is inherent ambiguity. To interpret the ambiguous Chinese discourse markers, we propose a semi-supervised framework to estimate the distribution of each Chinese discourse marker from a large-sized corpus, the ClueWeb09. This semi-supervised framework with the estimated distributions finally improve the performance of Chinese discourse relation recognition.
Discourse relations and sentiment polarities are interactive in text. We investigate their correlation with ClueWeb09. A moderate-sized data annotated by human are analyzed and compared with the huge data heuristically labeled by machine. As a result, the association between sentiment and discourse is validated.
In this dissertation, we focus on the four-way discourse relation classification. We will investigate the finer-grained classification on discourse relations in the future. In addition, we will further tackle the issue of Chinese discourse parsing at paragraph level and document level.

口試委員會審定書 i
誌謝 ii
中文摘要 iii
ABSTRACT v
CONTENTS vii
LIST OF FIGURES x
LIST OF TABLES xi
Chapter 1. Introduction 1
1.1. Discourse Relation Analysis 1
1.2. Types of Discourse Relations 3
1.3. Discourse Markers 7
1.4. Chinese Discourse Relations 8
1.5. Research Goals 9
1.6. Organization 10
Chapter 2. Related Work 11
2.1. Resources 11
2.2. Discourse Relation Recognition in English 13
2.3. Discourse Relation Recognition in Chinese 15
2.4. Discourse Relations and Sentiment Polarities 18
2.5. Discourse Parsing 19
Chapter 3. Discourse Relation Recognition 21
3.1. Dataset 21
3.2. Method 24
3.3. Experiments and Discussion 25
3.3.1 Results of Inter-sentential Discourse Relation Recognition 26
3.3.2 Results of Intra-sentential Discourse Relation Recognition 29
3.4. Summary 31
Chapter 4. Discourse Relation and Parsing 33
4.1. Dataset 33
4.2. Methods 36
4.3. Experiments and Discussion 39
4.4. Summary 45
Chapter 5. Discourse Relation and Sentiment Polarity 47
5.1. Linguistic Resources 47
5.2. Analysis on Human Annotated Data 48
5.2.1 Annotation 48
5.2.2 Overview of the Annotated Corpus 49
5.2.3 Frequent Discourse Markers 52
5.2.4 Association between Discourse Relation and Sentiment Polarity 54
5.3. Analysis on Large-scale Data 59
5.3.1 A Lexicon-based Method for Sentiment Analysis 59
5.3.2 Evaluation 60
5.3.3 Results and Discussion 62
5.4. Summary 65
Chapter 6. Interpretation of Discourse Markers 67
6.1. Types of Discourse Markers 69
6.2. Dataset 71
6.3. Ambiguity of Chinese Discourse Markers 72
6.3.1 Performance of Using Discourse Marker Dictionary 72
6.3.2 Thesaurus Alignment 73
6.4. A Semi-Supervised Method 77
6.4.1 Linguistic Features 78
6.4.2 A Semi-supervised Learning Algorithm 79
6.5. Experimental Results 81
6.6. Further Analyses on a Big Dataset 85
6.7. Summary 90
Chapter 7. Conclusion 92
REFERENCES 94

Nicholas Asher and Alex Lascarides. 1995. Lexical Disambiguation in a Discourse Context. Journal of Semantics, 12(1):69-108, Oxford University Press.
Adam A Augustine, Matthias R. Mehl and Randy J. Larsen. 2011. A Positivity Bias in Written and Spoken English and Its Moderation by Personality and Gender. Social Psychological and Personality Science, 2(5): 508-515.
Or Biran and Kathleen McKeown. 2013. Aggregated Word Pair Features for Implicit Discourse Relation Disambiguation. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 69-73, Sofia, Bulgaria.
Lynn Carlson and Daniel Marcu. 2001. Discourse Tagging Reference Manual. http://www.isi.edu/~marcu/discourse/tagging-ref-manual.pdf
Lynn Carlson, Daniel Marcu, and Mary E. Okurowski. 2002. RST Discourse Treebank Linguistic Data Consortium, Philadelphia.
Chih-Chung Chang and Chih-Jen Lin. 2011. LIBSVM : A Library for Support Vector Machines. ACM Transactions on Intelligent Systems and Technology, 2:27:1--27:27.
Hsin-Hsi Chen. 1994. The Contextual Analysis of Chinese Sentences with Punctuation Marks. Literal and Linguistic Computing, 9(4):281-289.
Shou-Yi Cheng. 2006. Corpus-Based Coherence Relation Tagging in Chinese Discourse. Master Thesis, National Chiao Tung University, Hsinchu, Taiwan.
Xianghui Cheng and Xiaolin Tian. 1989. Xian dai Han yu (現代漢語), San lian shu dian (三聯書店), Hong Kong.
CMU 2009. ClueWeb09, http://lemurproject.org/ clueweb09.php/
Leon Derczynski and Robert Gaizauskas. 2013. Temporal Signals Help Label Temporal Relations. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 645-650, Sofia, Bulgaria.
Ann Devitt and Khurshid Ahmad. 2007. Sentiment polarity identification in financial news: a cohe-sion-based approach. In Proceedings of the 45th Annual Meeting of the Association of Computa-tional Linguistics (ACL 2007), pages 984-991, Prague, Czech Republic.
Vanessa Wei Feng and Graeme Hirst. 2012. Text-level Discourse Parsing with Rich Linguistic Features. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 60-68, Jeju Island, Korea.
David Garcia, Antonios Garas, and Frank Schweitzer. 2012. Positive Words Carry Less Information than Negative Words. EPJ Data Science: A SpringerOpen Journal, 1(3):1-12.
Hugo Hernault, Danushka Bollegala, and Mitsuru Ishizuka. 2010a. A Semi-Supervised Approach to Improve Classi&;#64257;cation of Infrequent Discourse Relations using Feature Vector Extension. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2010), pages 399-409.
Hugo Hernault, Danushka Bollegala, and Mitsuru Ishizuka. 2011. Semi-supervised Discourse Relation Classi&;#64257;cation with Structural Learning. In Proceedings of the 12th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing 2011), Volume Part I, pages 340-352.
Hugo Hernault, Helmut Prendinger, David A. duVerle, and Mitsuru Ishizuka. 2010b. HILDA: A Discourse Parser Using Support Vector Machine Classification. Dialogue and Discourse, 1(3): 1-33.
Jerry R. Hobbs. 1985. On the Coherence and Structure of Discourse, Report No. CSLI-85-37, Center for the Study of Language and Information, Stanford University. http://www.isi.edu/~hobbs/ocsd.pdf
Eduard H. Hovy and Elisabeth Maier. 1992. Parsimonious or Profligate: How Many and Which Discourse Structure Relations? No. ISI/RR-93-373. Information Sciences Institute, University of Southern California, Marina del Rey.
Chu-Ren Huang and Keh-jiann Chen. 1992. A Chi-nese corpus for linguistics research. In Proceedings of the 14th International Conference on Computational Linguistics, pages 1214-1217, France.
Hen-Hsen Huang, Kai-Chun Chang, and Hsin-Hsi Chen. 2013a. Modeling Human Inference Process for Textual Entailment Recognition. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 446-450, Sofia, Bulgaria.
Hen-Hsen Huang, Tai-Wei Chang, Huan-Yuan Chen, and Hsin-Hsi Chen. 2014a. Interpretation of Chinese Discourse Connectives for Explicit Discourse Relation Recognition. To appear in Proceedings of the 25th International Conference on Computational Linguistics (COLING 2014), Dublin, Ireland.
Hen-Hsen Huang and Hsin-Hsi Chen. 2011a. Pause and Stop Labeling for Chinese Sentence Boundary Detection. In Proceedings of the International Conference Recent Advances in Natural Language Processing 2011, pages 146-153, Hissar, Bulgaria.
Hen-Hsen Huang and Hsin-Hsi Chen. 2011b. Chinese Discourse Relation Recognition. In Proceedings of the 5th International Joint Conference on Natural Language Processing (IJCNLP 2011), pages 1442-1446, Chiang Mai, Thailand.
Hen-Hsen Huang and Hsin-Hsi Chen. 2012a. Contingency and Comparison Relation Labeling and Structure Prediction in Chinese Sentences. In Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL 2012), pages 261-269, Seoul, South Korea.
Hen-Hsen Huang and Hsin-Hsi Chen. 2012b. An Annotation System for Development of Chinese Discourse Corpus. In Proceedings of the 24th International Conference on Computational Linguistics (COLING 2012) Demonstration Papers, pages 223-230.
Chu-Ren Huang, Feng-Yi Chen, Keh-Jiann Chen, Zhao-ming Gao, and Kuang-Yu Chen. 2000. Sinica Treebank: Design Criteria, Annotation Guidelines, and On-line Interface. In Proceedings of 2nd Chinese Language Processing Workshop (Held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics, ACL-2000), pages 29-37.
Hen-Hsen Huang, Chi-Hsin Yu, Tai-Wei Chang, Cong-Kai Lin, and Hsin-Hsi Chen. 2013b. Analyses of the Association between Discourse Relation and Sentiment Polarity with a Chinese Human-Annotated Corpus. In Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse, pages 70-78, Sofia, Bulgaria.
Hen-Hsen Huang, Chi-Hsin Yu, Tai-Wei Chang, Cong-Kai Lin, and Hsin-Hsi Chen. 2014b. Web-Based Analysis of Chinese Discourse Markers for Opinion Mining. To appear in Proceedings of the 2014 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2014), Warsaw, Poland.
Ting-Hao Huang, Ho-Cheng Yu and Hsin-Hsi Chen. 2012. Modeling pollyanna phenomena in Chinese sentiment analysis. In Proceedings of the 24th International Conference on Computational Linguistics, Demo, pages 231-238, Mumbai, India.
Ben Hutchinson. 2004. Acquiring the meaning of discourse markers. In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL 2004), pages 684-691, Barcelona, Spain.
Shafiq Joty, Giuseppe Carenini, and Raymond Ng. 2012. A Novel Discriminative Framework for Sentence-Level Discourse Analysis. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pages 904-915, Jeju Island, Korea.
Shafiq Joty, Giuseppe Carenini, Raymond Ng, and Yashar Mehdad. 2013. Combining Intra- and Multi-sentential Rhetorical Parsing for Document-level Discourse Analysis. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 486-496, Sofia, Bulgaria.
Soo-Min Kim and Eduard Hovy. 2004. Determining the sentiment of opinions. In Proceedings of the 20th International Conference on Computational Linguistics (COLING-04), pages 1367-1373, Geneva, Switzerland.
Lun-Wei Ku and Hsin-Hsi Chen. 2007. Mining Opinions from the Web: Beyond Relevance Retrieval. Journal of American Society for Information Science and Technology, 58(12): 1838-1850
Lun-Wei Ku, Ting-Hao Huang, and Hsin-Hsi Chen. 2009. Using morphological and syntactic structures for Chinese opinion analysis. In Proceedings of Conference on Empirical Methods in Natural Language Processing, pages 1260-1269, Singapore.
Lun-Wei Ku, Ting-Hao Huang, and Hsin-Hsi Chen. 2011. Predicting opinion dependency relations for opinion analysis. In Proceedings of the 5th International Joint Conference on Natural Language Processing, pages. 345-353, Chiang Mai, Thailand.
Angeliki Lazaridou, Ivan Titov, and Caroline Sporleder. 2013. A Bayesian Model for Joint Unsupervised Induction of Sentiment, Aspect and Discourse Representations. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1630-1639, Sofia, Bulgaria.
Charles N. Li, Sandra A. Thompson. 1981. Mandarin Chinese: A Functional Reference Grammar. University of California Press.
Ziheng Lin, Min-Yen Kan, and Hwee Tou Ng. 2009. Recognizing implicit discourse relations in the Penn Discourse Treebank. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing (EMNLP 2009), pages 343-351.
Ziheng Lin, Hwee Tou Ng, and Min-Yen Kan. 2011. Automatically Evaluating Text Coherence Using Discourse Relations. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011), pages 997-1006.
Shuxiang Lu. 2007. Eight Hundred Words of The Contemporary Chinese (Xian dai Han yu Ba bai Ci), China Social Sciences Press.
Daniel Marcu and Abdessamad Echihabi. 2002. An Unsupervised Approach to Recognizing Discourse Relations. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL 2002), pages 368-375, Philadelphia, USA.
Claudiu Mihaila and Sophia Ananiadou. 2013. What causes a causal relation? Detecting Causal Triggers in Biomedical Scientific Discourse. In 51st Annual Meeting of the Association for Computational Linguistics Proceedings of the Student Research Workshop, pages 38-45, Sofia, Bulgaria.
Ruslan Mitkov. 2010. Discourse Processing. In The Handbook of Computational Linguistics and Natural Language Processing (eds A. Clark, C. Fox and S. Lappin), pages, 599-629, Wiley-Blackwell, Oxford, UK. doi: 10.1002/9781444324044.ch21
Bo Pang and Lillian Lee. 2008. Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2(1-2): 1-135.
Emily Pitler and Ani Nenkova. 2009. Using Syntax to Disambiguate Explicit Discourse Connectives in Text. In Proceedings of the ACL-IJCNLP 2009 Conference Short Papers, pages 13-16, Suntec, Singapore.
Emily Pitler, Mridhula Raghupathy, Hena Mehta, Ani Nenkova, Alan Lee, and Aravind Joshi. 2008. Easily Identifiable Discourse Relations. In Proceedings of the 22th International Conference on Computational Linguistics (COLING 2008) Poster Papers.
Livia Polanyi. 1988. A Formal Model of the Structure of Discourse. Journal of Pragmatics, 12(5-6):601-638.
Rashmi Prasad, Nikhil Dinesh, Alan Lee, Eleni Miltsakaki, Livio Robaldo, Aravind Joshi, and Bonnie Webber. 2007. The Penn Discourse Treebank 2.0 Annotation Manual. The PDTB Research Group.
Rashmi Prasad, Nikhil Dinesh, Alan Lee, Eleni Miltsakaki, Livio Robaldo, Aravind Joshi, and Bonnie Webber. 2008. The Penn Discourse TreeBank 2.0. In Proceedings of the 6th Language Resources and Evaluation Conference (LREC 2008), pages 2961-2968, Marrakech, Morocco.
Charlotte Roze, Laurence Danlos, and Philippe Muller. 2010. LEXCONN: a French Lexicon of Discourse Connectives. In Proceedings of the 8th International Workshop on Multidisciplinary Approaches to Discourse (MAD 2010), Moissac.
Paul Rozin, Loren Berman, and Edward Royzman. 2010. Biases in Use of Positive and Negative Words Across Twenty Natural Languages. Cognition and Emotion, 24(3): 536-548.
Ted J. M. Sanders, Wilbert P. M. Spooren, and Leo G. M. Noordman. 1992. Toward a Taxonomy of Coherence Relations. Discourse Processes, 15(1):1-35.
Radu Soricut and Daniel Marcu. 2003. Sentence level discourse parsing using syntactic and lexical information. In Proceedings of Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics (HLT/NAACL 2003), pages 149-156, Edmonton, Canada.
Karl Sornig. 1989. Some remarks on linguistic strategies of persuasion. Language, Power and Ideology. Studies in Political Discourse, pages 95-115.
Caroline Sporleder and Alex Lascarides. 2008. Using Automatically Labelled Examples to Classify Rhetorical Relations: A Critical Assessment. Natural Language Engineering, 14(3):369-416, Cambridge University Press.
Maite Taboada, Julian Brooke, Milan Tofiloski, Kimberly Voll, and Manfred Stede. 2011. Lexicon-Based Methods for sentiment analysis. Computational Linguistics, 37(2): 267-307.
WenTing Wang, Jian Su, and Chew Lim Tan. 2010. Kernel Based Discourse Relation Recognition with Temporal Ordering Information. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL 2010), Uppsala, Sweden, July.
Fei Wang, Yunfang Wu, and Likun Qiu. 2012. Exploiting Discourse Relations for Sentiment Analysis. In Proceedings of COLING 2012: Posters, pages 1311-1320, Mumbai, India.
Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, and Ann Houston. 2011. OntoNotes Release 4.0 LDC2011T03. Web Download. Philadelphia: Linguistic Data Consortium.
Florian Wolf and Edward Gibson. 2005. Representing Discourse Coherence: A Corpus-Based Analysis. Computational Linguistics, 31(2): 249-287.
Fu-yi Xing. 2002. Xiandai Hanyu Fuju Yanjiu (現代漢語複句研究), Shangwu Publishing Company (商務印書館), Beijing.
Nianwen Xue. 2005. Annotating Discourse Connectives in the Chinese Treebank. In Proceedings of the Workshop on Frontiers in Corpus Annotation II: Pie in the Sky, pages 84-91.
Yaqin Yang and Nianwen Xue. 2012. Chinese Comma Disambiguation for Discourse Analysis. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 786-794, Jeju Island, Korea.
Chi-Hsin Yu, Yi-jie Tang and Hsin-Hsi Chen. 2012. Development of a Web-scale Chinese Word N-gram Corpus with Parts of Speech Information. In Proceedings the 8th International Conference on Language Resources and Evaluation (LREC 2012), pages 320-324, Istanbul, Turkey.
Muyu Zhang, Bing Qin, and Ting Liu. 2013a. Chinese Discourse Relation System and Annotation Analysis. Journal of Chinese Information Processing.
Muyu Zhang, Yuan Song, Bing Qin, and Ting Liu. 2013b. Chinese Discourse Relation Recognition. Journal of Chinese Information Processing.
Lanjun Zhou, Wei Gao, Binyang Li, Zhongyu Wei, and Kam-Fai Wong. 2012. Cross-lingual Identification of Ambiguous Discourse Connectives for Resource-Poor Language. In Proceedings of COLING 2012, pages 1409-1418.
Lanjun Zhou, Binyang Li, Wei Gao, Zhongyu Wei, and Kam-Fai Wong. 2011. Unsupervised Discovery of Discourse Relations for Eliminating Intra-sentence Polarity Ambiguities. In Proceedings of EMNLP 2011, pages 162-171.
Zhi-Min Zhou, Yu Xu, Zheng-Yu Niu, Man Lan, Jian Su, and Chew Lim Tan. 2010. Predicting discourse connectives for implicit discourse relation recognition. In Proceedings of the 23rd International Conference on Computational Linguistics (COLING 2010): Posters, pages 1507-1514.
Yuping Zhou and Nianwen Xue. 2012. PDTB-style Discourse Annotation of Chinese Text. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (ACL 2012), pages 67-77, Jeju Island, Korea.
Qiang Zhou and Jingbo Zhu. 2010. Chinese Syntactic Parsing Evaluation. In Proceedings of CIPS-SIGHAN Joint Conference on Chinese Language Processing (CLP-2010), pages 286-295, Beijing.

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top