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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 資訊網路與多媒體研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/17058
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor許永真(Jane Yung-Jen Hsu)
dc.contributor.authorGeorge Changen
dc.contributor.author張衡zh_TW
dc.date.accessioned2021-06-07T23:54:58Z-
dc.date.copyright2013-09-07
dc.date.issued2013
dc.date.submitted2013-08-29
dc.identifier.citation[1] E. Agichtein and L. Gravano. Snowball:extracting relations from large plain-text col- lections. In Proceedings of the 5th ACM International Conference on Digital Libraries, pages 85–94, 2000.
[2] C.-C. Chang and C.-J. Lin. LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2:27:1–27:27, 2011. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.
[3] X. Ding, B. Liu, and P. S. Yu. A holistic lexicon-based approach to opinion mining. In Proceedings of the First ACM International Conference on Web Search and Web Data Mining (WSDM 2008), pages 231–240, 2008.
[4] A. B. Goldberg, N. Fillmore, D. Andrzejewski, Z. Xu, B. Gibson, and X. Zhu. May all your wishes come true: A study of wishes and how to recognize them. In Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pages 263–271, June 2009.
[5] M. Hu and B. Liu. Mining and summarizing customer reviews. In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2004), pages 168–177, 2004.
[6] J. Ramanand, K. Bhavsar, and N. Pedanekar. Wishful thinking - finding suggestions and ’buy’ wishes from product reviews. In Proceedings of the NAACL HLT 2010Workshop on Computational Approaches to Analysis and Generation of Emotion inText, pages 54–61, June 2010.
[7] G. S. Speer. Oral and written wishes of rural and city school children. 10:151––155,1939.
[8] Y.-F. Tsai and K.-J. Chen. Reliable and cost-e↵ective pos-tagging. International Journal of Computational Linguistics and Chinese Language Processing, 9:83–96, 2004.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/17058-
dc.description.abstract夢想與希望自古以來象徵著人類的價值與前進的動力。在網路社群(Social Media)與微網誌盛行之時,網路的隔世造就世人輕易於雲端坦白露念,因此期許與願望不再受限於噴泉、宗教神氏或流星殞落之時。收集分析為網誌之中的研究願望,不但能從中發探究商場產品的趨勢與潛在市場,也能挖掘特殊需求並提供解決方案,受惠企業、百姓與弱勢族群。藉由分析一個活躍於港澳台區域的 Linkwish 行動願望社群網站。我們得以歸納了解願望之特性與內容,並以支援向量機(Support Vector Machine)搭配多種語言特徵作為依據,偵測網誌是否為願望,並藉由圖樣分析取得其目標資訊,終將願望分類至知識庫(Knowledge Base)做為具有認知意義的分類。以便用於檢索與統計。本篇論文使用語言特徵能提升願望偵測準確達0.95 AUC,對於精簡明確的願望能準確分析出願望目標資訊,並分類至知識庫。zh_TW
dc.description.abstractPeople have wishes and sometimes share their wishes in social media, hoping to get greetings or to find partners with the same wishes. By collecting and analyzing those wishes, we may find out not only the trend of common wishes, but also the needs of individuals. This paper presents a preliminary study of Chinese wish analysis. We provide analysis on the data from Linkwish, which is a micro social network for wish sharing with users mainly from Taiwan, Hong Kong, and Macao. Then, we use SVM with various types of features to classify these messages as wish or not, extract wish target information, and categorized wish into knowledge base. Our experimental results show that some features in wish detector can achieve average areas under precision-recall curves higher than 0.95 in 10-fold cross validation, And extract target, link into knowledge base from simple wishes.en
dc.description.provenanceMade available in DSpace on 2021-06-07T23:54:58Z (GMT). No. of bitstreams: 1
ntu-102-R99944002-1.pdf: 3071532 bytes, checksum: 10a451c5ddddc2b0591848ee5fd17ea3 (MD5)
Previous issue date: 2013
en
dc.description.tableofcontentsAcknowledgments i
中文摘要 iii
Abstract v
1 Introduction 1
1.1 Motivation.................................. 1
1.2 Challenges in Wish Analysis ........................ 2
1.3 Problem Definition ............................. 2
1.4 Proposed Solution.............................. 3
1.5 Thesis Organization............................. 4
2 Background and Related Work 5
2.1 Definition of Wish ............................. 5
2.2 Chinese NLP ................................ 6
2.3 Support Vector Machines.......................... 6
2.4 Knowledge Base .............................. 6
2.5 Related Work ................................ 6
3 Data Set 9
3.1 Linkwish DataSet.............................. 9
3.2 Observation of Linkwish .......................... 9
4 Wish Analyzer Architecture 15
4.1 Chinese NLP Processor........................... 15
4.2 Wish Detector................................ 16
4.2.1 Manual Label Features....................... 16
4.2.2 Novel NLP Pattern Features .................... 17
4.2.3 N-gram Base Features ....................... 17
4.3 Target Extractor............................... 18
4.4 Entity Categorizer.............................. 19
5 Experiment Design and Result 23
5.1 Features in SVM Wish Detector ...................... 23
5.2 Intent-Verb inTarget Extractor ....................... 24
5.3 Entity Categorizer.............................. 26
6 Conclusion and Future Work 33
6.1 Summary .................................. 33
6.2 FutureWork................................. 33
Bibliography 35
dc.language.isoen
dc.subject願望zh_TW
dc.subject自然語言處理zh_TW
dc.subject社群網路zh_TW
dc.subjectNLPen
dc.subjectlinkwishen
dc.subjectSocial Mediaen
dc.title以自然語言處理分析社群網路願望之研究zh_TW
dc.titleDetecting Chinese Wish Messages in Social Media and Categorizing into Knowledge Baseen
dc.typeThesis
dc.date.schoolyear101-2
dc.description.degree碩士
dc.contributor.oralexamcommittee陳信希(Hsin-Hsi Chen),林守德(Shou-De Lin),蔡宗翰(Tzong-Han Tsai),黃漢申(Han-Shen Huang)
dc.subject.keyword自然語言處理,社群網路,願望,zh_TW
dc.subject.keywordlinkwish,Social Media,NLP,en
dc.relation.page36
dc.rights.note未授權
dc.date.accepted2013-08-29
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept資訊網路與多媒體研究所zh_TW
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