A Research on Opinion Analysis for Book Reviews

Автор: Na Zhai, Fang Yuan, Yu Wang

Журнал: International Journal of Education and Management Engineering(IJEME) @ijeme

Статья в выпуске: 6 vol.2, 2012 года.

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Product reviews are not only useful for trade companies to improve the quality of products, but also helpful for customers to purchase products reasonably, thus product reviews mining is valuable in application and research. In this paper, we devote the research on book reviews. We first propose a polarity dictionary construction method based on the improved CHI, and realizes dynamic addition of the dictionary; Second, the polarity calculation formula of the transitional complex sentences is improved to be applicable to book reviews. Considering that some book reviews have titles and these titles generally express the reviewers’ opinion tendency, so we further propose an opinion polarity analysis method based on the titles and the improved polarity calculation formula of the heavy transitional sentences. The experimental results show that the approach proposed in this paper is effective.

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Dynamic dictionary, title polarity, polarity analysis, heavy transitional sentence

Короткий адрес: https://sciup.org/15013706

IDR: 15013706

Список литературы A Research on Opinion Analysis for Book Reviews

  • WU Xing, HE Zhong-shi and HUANG Yong-wen. Survey on Product Review Mining. Computer Engineering and Applications, vol. 44, pp. 37-41, 2008. (in Chinese)
  • Hu M, and Liu B. Mining Opinion Features in Customer Review. To appear in AAAI’04, pp. 755-760, 2004.
  • Hu M, and Liu B. Mining and Summarizing Customer Reviews[C]. KDD’04, pp. 168-177, 2004.
  • Liu B, Hu M, Cheng J. Opinion Observer: Analyzing and Comparing Opinions on the Web. In Proceedings of the 14th international conference on world wide web, Chiba, Japan, pp. 342-351, 2005.
  • Gamgarn Somprasertsri, Pattarachi Lalitrojwong. Mining Feature-Opinion in Online Customer Reviews for Opinion Summarization. Journal of Universal Computer Science, vol. 16, pp. 938-955, 2010.
  • Wei Wei, Hongyan Liu, Jun He, Hui Yang, Xiaoyong Du. Extracting Feature and Opinion Words Effectively from Chinese Product Reviews. International Conference on Fuzzy Systems and Knowledge Discovery, pp. 170-174, 2008.
  • Yun-qing Xia, Rui-reng XU, Kam-fai Wong and Fang Zheng. The Unified Collocation Framework for Opinion Mining. Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, 2007.
  • Xiao Wei. Semantic Based Sentiment Classification on Blog Community. Shanghai: Shanghai Jiaotong University, 2007. (in Chinese)
  • Hinrich Schutze, David A.Hull and Jan O. Pedersen. A Comparison of Classifiers and Document Representations for the Routing Problem. In Proceedings of SIGIR.95, 18’h ACM International Conference on Research and Development in Information Retrieval, pp. 229-237, 1995.
  • Yu Wang, Zheng-Ou Wang. Text Categorization Rule Extraction Based on Fuzzy Decision Tree. Machine Learning and Cybernetics, Proceedings of 2005 International Conference on, vol. 4, 2122-2127, 2005.
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