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浙江大学学报(工学版)
J4  2010, Vol. 44 Issue (11): 2188-2193    DOI: 10.3785/j.issn.1008973X.2010.11.026
计算机科学技术     
基于传播的产品属性抽取
仇光,郑淼,卜佳俊,史源,陈纯
浙江大学 计算机学院 浙江省服务机器人重点实验室,浙江 杭州 310027
Propagation based product feature extraction
QIU Guang, ZHENG Miao, BU Jia-jun, SHI Yuan, CHEN Chun
College of Computer Science,  Zhejiang Key Laboratory of Service Robot, Zhejiang University, Hangzhou 310027, China
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摘要：

针对意见挖掘中产品意见对象的获取问题,提出一种基于传播(propagation)思想的产品属性抽取方法.该方法利用产品属性与意见词(opinion word)之间,以及产品属性本身和意见词本身的关系,通过定义的规则,抽取产品属性.对属性与意见词之间的关系采用依存语法进行描述.产品属性和意见词的抽取过程不断迭代,直至无新的属性可抽取.同时,为消除传播过程中引入的噪音,提出3种相应的噪音消除策略.实验结果表明,该方法比传统的产品属性抽取方法有更高的准确率和召回率.
Abstract:

To extract the targets of product opinions, we proposed a novel propagation based approach to extract product features. This approach explored the syntactic relations of opinion words and product features, opinion words and opinion words, feature and features, and defined rules to extract the features. The relations between features and opinion words are described in dependency grammar. This propagation process of feature and opinion word extraction went on until no new features could be extracted. Meanwhile, to remove possible noises introduced in the propagation, three pruning strategies were introduced. Experimental results show that it outperforms two stateoftheart existing approaches．
出版日期: 2010-12-23
:  TP 391.1  
基金资助:

 国家科技支撑计划资助项目（2008BAH26B00）;新世纪优秀人才支持计划资助项目（NCET090685）.
通讯作者: 卜佳俊(1973－)，男，教授.     E-mail: bjj@zju.edu.cn
作者简介: 仇光(1983-)，男，浙江象山人，博士生，主要从事数据，信息检索方面的研究.E-mail: qiuguang@zju.edu.cn
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引用本文:

仇光,郑淼,卜佳俊,史源,陈纯. 基于传播的产品属性抽取[J]. J4, 2010, 44(11): 2188-2193.

QIU Guang, ZHENG Miao, BU Jia-jun, SHI Yuan, CHEN Chun. Propagation based product feature extraction. J4, 2010, 44(11): 2188-2193.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008973X.2010.11.026    或    http://www.zjujournals.com/eng/CN/Y2010/V44/I11/2188

［1］ HATZIVASSILOGLOU V, MCKEOWN K R. Predicting the semantic orientation of adjectives ［C］∥ Proceedings of ACL’97. Madrid: ACL, 1997: 174-181．
［2］ HU Mingqing, LIU Bing. Mining and summarizing customer reviews ［C］∥ Proceedings of SIGKDD’04. Seattle: ACM, 2004: 168-177．
［3］ KIM S M, HOVY E. Determining the sentiment of opinions ［C］∥ Proceedings of COLING’04. Geneva: ACL, 2004: 1367-1373．
［4］ MEI Qiaozhu, LING Xu, WONDRA M, et al. Topic sentiment mixture: modeling facets and opinions in weblogs ［C］∥Proceedings of WWW’07. Banff: ACM, 2007: 171-180．
［5］ PANG Bo, LEE L, VAITHYANATHAN S. Thumbs up？ sentiment classification using machine learning techniques ［C］∥Proceedings of EMNLP’02. Pennsylvania: ACL, 2002: 79-86．
［6］ POPESCU A M, ETZIONI O. Extracting product features and opinions from reviews ［C］∥Proceedings of EMNLP’05. Vancouver: ACL, 2005: 339-346．
［7］ 姚天昉,程希文,徐飞玉,等. 文本意见挖掘综述 ［J］. 中文信息学报,2008,22(3): 71-80．
YAO Tianfang, CHENG Xiwen, XU Feiyu, et al. A survey of opinion mining for texts ［J］. Journal of Chinese Information Processing, 2008, 22(3): 71-80.
［8］ SEKI Y. Opinion holder extraction from author and authority viewpoints ［C］∥Proceedings of SIGIR’07. Amsterdam: ACM, 2007: 841-842．
［9］ LU Yue, ZHAI Chengxiang. Opinion integration through semisupervised topic modeling ［C］∥ Proceedings of WWW’08. Beijing: ACM, 2008: 121-130．
［10］ MEI Qiaozhu, CAI Deng, ZHANG Duo, et al. Topic modeling with network regularization ［C］∥ Proceedings of WWW’08. Beijing: ACM, 2008: 101-110．
［11］ KU Lunwei, LIANG Yuting, CHEN Hsinhsi. Opinion extraction, summarization and tracking in news and blog corpora ［C］∥AAAI Spring Symposia 2006 on Computational Approaches to Analyzing Weblogs. Boston: AAAI, 2006: 100-107．
［12］ LEE T Y. Needsbased analysis of online customer reviews ［C］∥ Proceedings of ICEC’07. Minneapolis: ACM, 2007: 311-317．
［13］ TAN Songbo, ZHANG Jin. An empirical study of sentiment analysis for chinese documents ［J］. Expert Systems with Applications, 2007, 34(4): 2622-2629．
［14］ TURNEY P. Thumbs up or thumbs down？ semantic orientation applied to unsupervised classification of reviews ［C］∥Proceedings of ACL’02. Pennsylvania: ACL, 2002: 417-424．
［15］ TURNEY P D, LITTMAN M L. Measuring praise and criticism: inference of semantic orientation from association ［J］. ACM Transactions on Information Systems, 2003, 21(4): 315-346．
［16］ YE Qiang, LIN Bin, LI Yijun. Sentiment classification for chinese reviews: a comparison between SVM and semantic approaches ［C］∥ The 4th International Conference on Machine Learning and Cybernetics. Guangzhou: IEEE, 2005: 2341-2346．
［17］ YE Qiang, SHI Wen, LI Yijun. Sentiment classification for movie reviews in chinese by improved semantic oriented approach ［C］∥ Proceedings of HICSS39. Hawaiian: IEEE, 2006: 53b-53b．
［18］ JACQUEMIN C, BOURIGAULT D. Term extraction and automatic indexing. In R. Mitkov, editor, Handbook of Computational Linguistics ［M］. London: Oxford University Press, 2001: 122.
［19］ JUSTESON J S, KATZ S M. Technical terminology: some linguistic properties and an algorithm for identification in text ［J］. Natural Language Engineering, 1995, 1(1): 9-27．

［20］ APPELT D E, HOBBS J R, BEAR J, et al. Fastus: a finitestate processor for information extraction from realworld text ［C］∥ Proceedings of IJCAI’93. Chambery: AAAI, 1993: 1172-1178．
［21］ GRISHMAN R, SUNDHEIM B. Message understanding conference6: a brief history ［C］∥ Proceedings of COLING’96. Copenhagen: ACL, 1996: 466-471．
［22］ RILOFF E. Automatically constructing a dictionary for information extraction tasks ［C］∥ Proceedings of AAAI’93. Washington: AAAI, 1993: 811-816．
［23］ RABINER L. A tutorial on hidden markov models and selected applications in speech recognition ［C］∥Proceedings of the IEEE. New York: IEEE, 1989, 77(2)．
［24］ RATNAPARKHI A. Learning to parse natural language with maximum entropy models \
[J\]. Machine Learning , 1999, 34 (13): 151-175．
［25］ LAFFERTY J, MCCALLUM A, PEREIRA F. Conditional random fields: probabilistic models for segmenting and labeling sequence data ［C］∥Proceedings of ICML’01. Williamstown: Morgan Kaufmann, 2001: 282-289．
［26］ JINDAL N, LIU Bing. Mining comparative sentences and relations ［C］∥ Proceedings of AAAI’06. Boston: AAAI, 2006: 1331-1336．
［27］ CHOMSKY N. Three models for the description of language ［J］. IRI Transactions on Information Theory, 1956, 2(3) :113-124．
［28］ CULOTTA A, SORENSEN J. Dependency tree kernels for relation extraction ［C］∥ Proceedings of ACL’04. Barcelona: ACL, 2004: 423-429．
［29］ PUNYAKANOK V, ROTH D, YIH W. Natural language inference via dependency tree mapping: an application to question answering ［J］. Computational Linguistics, 2004, 6(9): 1-10.
［30］ LIN Dekang. Automatic retrieval and clustering of similar words ［C］∥Proceedings of ACL’98. Montreal: ACL, 1998: 768-774．
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