Abstract
This paper addresses the task of extracting opinions from a given document collection. Assuming that an opinion can be represented as a tuple 〈Subject, Attribute, Value〉, we propose a computational method to extract such tuples from texts. In this method, the main task is decomposed into (a) the process of extracting Attribute-Value pairs from a given text and (b) the process of judging whether an extracted pair expresses an opinion of the author. We apply machine-learning techniques to both subtasks. We also report on the results of our experiments and discuss future directions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Dave, K., Lawrence, S., Pennock, D.M.: Mining the peanut gallery: opinion extraction and semantic classification of product reviews. In: Proc. of the 12th International World Wide Web Conference, pp. 519–528 (2003)
Pang, B., Lee, L.: A sentiment education: Sentiment analysis using subjectivity summarization based on minimum cuts. In: Proc. of the 42nd Annual Meeting of the Association for Computational Linguistics, pp. 271–278 (2004)
Turney, P.D.: Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews. In: Proc. of the 40th Annual Meeting of the Association for Computational Linguistics, pp. 417–424 (2002)
Kanayama, H., Nasukawa, T.: Deeper sentiment analysis using machine translation technology. In: Proceedings of the 20th International Conference on Computational Linguistics, pp. 494–500 (2004)
Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proc. of the Tenth International Conference on Knowledge Discovery and Data Mining, pp. 168–177 (2004)
Tateishi, K., Ishiguro, Y., Fukushima, T.: Opinion information retrieval from the internet. IPSJ SIGNL Note 144-11, 75–82 (2001) (in Japanese)
Tateishi, K., Fukushima, T., Kobayashi, N., Takahashi, T., Fujita, A., Inui, K., Matsumoto, Y.: Web opinion extraction and summarization based on viewpoints of products. IPSJ SIGNL Note 163, 1–8 (2004) (in Japanese)
Murano, S., Sato, S.: Automatic extraction of subjective sentences using syntactic patterns. In: Proc. of the Ninth Annual Meeting of the Association for Natural Language Processing, pp. 67–70 (2003) (in Japanese)
Mitkov, R.: Factors in anaphora resolution: they are not the only things that matter. a case study ba sed on two different approaches. In: Proc. of the ACL 1997/EACL 1997 Workshop on Operational Factors in Practical, Robust Anaph ora Resolution. (1997)
Baldwin, B.: CogNIAC: A Discourse Processing Engine. PhD thesis, Department of Computer and Information Sciences, University of Pennsylvania (1995)
Nakaiwa, H., Shirai, S.: Anaphora resolution of japanese zero pronouns with deictic reference. In: Proceedings of the 16th International Conference on Computational Linguistics (COLING), pp. 812–817 (1996)
Grosz, B.J., Joshi, A.K., Weinstein, S.: Centering: A framework for modeling the local coherence of discourse. Computational Linguistics 21, 203–226 (1995)
Kameyama, M.: A property-sharing constraint in centering. In: Proceedings of the 24th Annual Meeting of the Association for Computational Linguistics, pp. 200–206 (1986)
Halliday, M.A.K., Hasan, R.: Cohesion in English. English Language Series,Title No.9. Longman (1976)
Soon, W.M., Ng, H.T., Lim, D.C.Y.: A machine learning approach to coreference resolution of noun phrases. Computational Linguistics 27, 521–544 (2001)
Ng, V., Cardie, C.: Improving machine learning approaches to coreference resolution. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL), pp. 104–111 (2002a)
Iida, R., Inui, K., Takamura, H., Matsumoto, Y.: Incorporating contextual cues in trainable models for coreference resolution. In: Proc. of the EACL Workshop on the Computational Treatment of Anaphora, pp. 23–30 (2003)
Ng, V.: Learning noun phrase anaphoricity to improve coreference resolution: Issues in representation and optimization. In: Proc. of the 42nd Annual Meeting of the Association for Computational Linguistics, pp. 152–159 (2004)
Iida, R., Inui, K., Matsumoto, Y., Sekine, S.: Noun phrase coreference resolution in japanese base on most likely antecedant candidates. Journal of Information Processing Society of Japan 46 (2005) (in Japanese)
Kobayashi, N., Inui, K., Matsumoto, Y., Tateishi, K., Fukushima, T.: Collecting evaluative expressions for opinion extraction. In: Su, K.-Y., Tsujii, J., Lee, J.-H., Kwong, O.Y. (eds.) IJCNLP 2004. LNCS, vol. 3248, pp. 596–605. Springer, Heidelberg (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kobayashi, N., Iida, R., Inui, K., Matsumoto, Y. (2006). Opinion Mining as Extraction of Attribute-Value Relations. In: Washio, T., Sakurai, A., Nakajima, K., Takeda, H., Tojo, S., Yokoo, M. (eds) New Frontiers in Artificial Intelligence. JSAI 2005. Lecture Notes in Computer Science(), vol 4012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11780496_49
Download citation
DOI: https://doi.org/10.1007/11780496_49
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35470-3
Online ISBN: 978-3-540-35471-0
eBook Packages: Computer ScienceComputer Science (R0)