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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/23020完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 林守德 | |
| dc.contributor.author | Jui-Yu Weng | en |
| dc.contributor.author | 翁睿妤 | zh_TW |
| dc.date.accessioned | 2021-06-08T04:38:06Z | - |
| dc.date.copyright | 2011-08-20 | |
| dc.date.issued | 2011 | |
| dc.date.submitted | 2011-08-17 | |
| dc.identifier.citation | [1] 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. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
[2] Mei-Yu Chen, Hsin-Ni Lin, Chang-An Shih, Yen-Ching Hsu, Pei-Yu Hsu, and Shu-Kai Hsieh. 2010. Classifying mood in plurks. In Proceedings of the 22nd Conference on Computational Linguistics and Speech Processing (ROCLING’10). pp. 172-183. [3] Dipanjan Das and Andre F.T. Martins. 2007. A Survey on Automatic Text Summarization. Literature Survey for the Language and Statistics II Course at CMU. [4] Helen Kwong and Neil Yorke-Smith. 2009. Detection of imperative and declarative question-answer pairs in email conversations. In Proceedings of the 21st international jont conference on Artifical intelligence (IJCAI'09). pp.1519-1524. [5] Chuanhan Liu, Yongcheng Wang, and Fei Zheng. 2006. Automatic Text Summarization for Dialogue Style. In Proceedings of the IEEE International Conference on Information Acquisition (ICIA’06). pp. 274-278. [6] Alexander Pak and Patrick Paroubek. 2010. Twitter as a Corpus for Sentiment Analysis and Opinion Mining. In Proceedings of International Conference on Language Resources and Evaluation (LREC’10). pp. 1320–1326. [7] Bo Pang and Lillian Lee. 2004. A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts. In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL’04). pp. 271-278. [8] Bo Pang and Lillian Lee. 2008. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1-2): 1-135. [9] Dragomir R. Radev, Eduard Hovy, and Kathleen McKeown. 2002. Introduction to the special issue on summarization. Computational Linguistics. pp. 399-408. [10] Satoshi Sekine and Chikashi Nobata. 2003. A Survey for Multi-Document Summarization. In Proceedings of North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT’03) on Text Summarization Workshop. pp.65-72. [11] Beaux Sharifi, Mark A. Hutton, and Jugal Kalita. 2010. Summarizing microblogs Automatically. In Proceedings of the Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT’10). pp.685-688. [12] Beaux Sharifi, Mark A. Hutton, and Jugal Kalita. 2010. Experiments in Microblog Summarization. In Proceedings of 2010 IEEE Second International Conference on Social Computing (SocialCom’10). pp.49-56. [13] Lokesh Shrestha and Kathleen McKeown. 2004. Detection of Question-Answer Pairs in Email Conversations. In Proceedings of the 23rd International Conference on Computational Linguistics (COLING’04). pp. 889-895. [14] Klaus Zechner. 2001. Automatic Generation of Concise Summaries of Spoken Dialogues in Unrestricted Domains. In Proceedings of the 24th ACM-SIGIR International Conference on Research and Development in Information Retrieval. pp. 199-207. [15] Klaus Zechner. 2002. Automatic Summarization of Open-Domain Multiparty Dialogues in Diverse Genres. Computational Linguistics, 28(4): 447-485. [16] Liang Zhou and Eduard Hovy. 2005. Digesting virtual geek culture: The summarization of technical internet relay chats, in Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL’05). pp. 298-305. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/23020 | - |
| dc.description.abstract | 本論文提出一個自動摘要系統，針對每一則微網誌上的訊息及回應產生簡明易讀的摘要。此系統的目的在於幫助微網誌使用者可以在大量的網路訊息中，有效率地擷取到重要且有意義的資訊。它採用了兩階段的摘要架構：第一個階段進行訊息的分類。每一則訊息都會被分為「疑問」、「連結分享」、「連結討論」以及「閒聊」等四種類型；第二個階段則是針對該訊息在上個階段被分配到的類別，採用適合該類的摘要策略及呈現方式。我們提出的策略共有「意見分析」、「回應分群」以及「回應相關度偵測」等三種。本論文在處理微網誌摘要的問題上，提出了一個不同於傳統文件摘要技術的觀點：透過不同系統之間的整合，電腦可以有能力產生出合於使用者目的之摘要，而不僅是訊息的過濾與壓縮。 | zh_TW |
| dc.description.abstract | This paper presents a system to summarize a microblog post and its responses with the goal to provide readers a more constructive and concise set of information for efficient digestion. We introduce a novel two-phase summarization scheme. In the first phase, the post plus its responses are classified into four categories based on the intention, Interrogation, URL-Sharing, URL-Discussion and Chat. For each type of post, in the second phase, we exploit different strategies, including Opinion Analysis, Response Group Clustering, and Response Relevancy Detection, to summarize and highlight critical information to display. This system provides an alternative thinking about machine-summarization: by utilizing AI approaches, computers are capable of constructing deeper and more user-friendly abstraction. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T04:38:06Z (GMT). No. of bitstreams: 1 ntu-100-R98922060-1.pdf: 1810465 bytes, checksum: 62f7c83b501d22d99daf7b6089f6a4d4 (MD5) Previous issue date: 2011 | en |
| dc.description.tableofcontents | 口試委員審定書 i
Acknowledgements ii 摘要 iii Abstract iv List of Figures vi List of Tables vii Chapter 1 Introduction 1 Chapter 2 Summarization Framework and Experiments 5 2.1 Plurk 5 2.2 Summarization Framework 6 2.2.1 Post Intention Classification 10 2.2.2 Opinion Analysis 14 2.2.3 Response Group Clustering 15 2.2.4 Response Relevance Detection 20 Chapter 3 System Demonstration 23 Chapter 4 Related Work 28 Chapter 5 Conclusion 31 References 32 | |
| dc.language.iso | en | |
| dc.subject | 系統整合 | zh_TW |
| dc.subject | 微網誌 | zh_TW |
| dc.subject | 自然語言處理 | zh_TW |
| dc.subject | 自動摘要 | zh_TW |
| dc.subject | 監督式學習 | zh_TW |
| dc.subject | Natural Language Processing | en |
| dc.subject | System Integration | en |
| dc.subject | Supervised Leaning | en |
| dc.subject | Microblog | en |
| dc.subject | Automatic Summarization | en |
| dc.title | IMASS：智慧型微網誌自動分析及摘要系統 | zh_TW |
| dc.title | IMASS: An Intelligent Microblog Analysis and Summarization System | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 99-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳信希,鄭卜壬,劉昭麟,張俊盛 | |
| dc.subject.keyword | 自動摘要,微網誌,自然語言處理,監督式學習,系統整合, | zh_TW |
| dc.subject.keyword | Automatic Summarization,Microblog,Natural Language Processing,Supervised Leaning,System Integration, | en |
| dc.relation.page | 34 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2011-08-17 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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|---|---|---|---|
| ntu-100-1.pdf 未授權公開取用 | 1.77 MB | Adobe PDF |
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