Abstract
Ontology itself is an explicitly defined reference model of application domains with the purpose of improving information consistency and knowledge sharing. It describes the semantics of a domain in both human-understandable and computer-processable way. Motivated by its success in the area of Information Extraction (IE), we propose an ontology-based approach for opinion mining. In general, opinion mining is quite context-sensitive, and, at a coarser granularity, quite domain dependent. This paper introduces a fine-grain approach for opinion mining, which uses the ontology structure as an essential part of the feature extraction process, by taking account the relations between concepts. The experiment result shows the benefits of exploiting ontology structure to opinion mining.
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References
Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up? sentiment classification using machine learning techniques. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP 2002 (2002)
Popescu, A.M., Etzioni, O.: Extracting product features and opinions from reviews. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP 2005 (2005)
Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proceedings of ACM SIGKDD conference, KDD 2004 (2004)
Kaji, N., Kitsuregawa, M.: Automatic construction of polarity-tagged corpus from html documents. In: Proceedings of the COLING/ACL on Main conference poster sessions, Association for Computational Linguistics Morristown, NJ, USA, pp. 452–459 (2006)
Hu, M., Liu, B.: Mining opinion features in customer reviews. In: Proceedings of AAAI, pp. 755–760 (2004)
Carenini, G., Ng, R., Pauls, A.: Interactive multimedia summaries of evaluative text. In: Proceedings of the 11th international conference on Intelligent user interfaces, pp. 124–131. ACM, New York (2006)
Ding, X., Liu, B.: The utility of linguistic rules in opinion mining. In: Proceedings of SIGIR 2007 (2007)
Gruber, T.R.: A translation approach to portable ontology specifications. Knowledge Acquisition 5, 199–220 (1993)
Pang, B.: Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales. Ann. Arbor. 100 (2005)
Riloff, E., Wiebe, J.: Learning extraction patterns for subjective expressions. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2003), pp. 105–112 (2003)
Turney, P., et al.: Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews. In: Proceedings of the 40th annual meeting of the Association for Computational Linguistics, pp. 417–424 (2002)
Gamon, M., Aue, A., Corston-Oliver, S., Ringger, E.: Pulse: Mining customer opinions from free text. In: Famili, A.F., Kok, J.N., Peña, J.M., Siebes, A., Feelders, A. (eds.) IDA 2005. LNCS, vol. 3646, pp. 121–132. Springer, Heidelberg (2005)
Dave, K., Lawrence, S., Pennock, D.: Mining the peanut gallery: Opinion extraction and semantic classification of product reviews. In: Proceedings of the 12th international conference on World Wide Web, pp. 519–528. ACM, New York (2003)
Hearst, M.A.: Direction-based text interpretation as an information access refinement, pp. 257–274 (1992)
Jacquemin, C.: Spotting and Discovering Terms through Natural Language Processing. MIT Press, Cambridge (2001)
Kobayashi, N., Inui, K., Matsumoto, Y.: Collecting evaluative express for opinion extraction. In: Proceedings of the International Joint Conference on Natural Language Processing, IJCNLP (2004)
Yi, J., Bunescu, T.N., Niblack, R.W.: Sentiment analyzer: extracting sentiments about a given topic using natural language processing techniques. In: Proceedings of IEEE International Conference on Data Mining, ICDM 2003 (2003)
Hatzivassiloglou, V., McKeown, K.: Predicting the semantic orientation of adjectives. In: Proceedings of ACL-EACL 1997 (1997)
Kanayama, H., Nasukawa, T.: Fully automatic lexicon expansion for domain-oriented sentiment analysis. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP 2006 (2006)
Esuli, A., Sebastiani, F.: Sentiwordnet: A publicly available lexical resource for opinion mining. In: Proceedings of 5th Conference on Language Resources and Evaluation, LREC 2006 (2006)
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Zhao, L., Li, C. (2009). Ontology Based Opinion Mining for Movie Reviews. In: Karagiannis, D., Jin, Z. (eds) Knowledge Science, Engineering and Management. KSEM 2009. Lecture Notes in Computer Science(), vol 5914. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10488-6_22
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DOI: https://doi.org/10.1007/978-3-642-10488-6_22
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