Abstract
Review mining is a part of web mining which focuses on getting main information from user review. State of the art review mining systems focus on identifying semantic orientation of reviews and providing sentences or feature scores. There has been little focus on understanding the rationale for the ratings that are provided. This paper presents our proposed RnR system for extracting rationale from online reviews and ratings. We have implemented the system for evaluation on online reviews for hotels from TripAdvisor.com and present extensive experimental evaluation that demonstrates the improved computational performance of our approach and the accuracy in terms of identifying the rationale. We have developed a web based system as well as web service based application to provide flexibility of accessing the rationale. Web based version of RnR system is available for testing from http://rnrsystem.com/RnRSystem. RnR system web service is available from http://rnrsystem.com/axis2/services/RnRData?wsdl.
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References
Hu, M., Liu, B.: Mining opinion features in customer reviews. In: Proceedings of National Conference of Artificial Intelligent, pp. 755–760. AAAI Press, San Jose (2004)
Sherchan, W., Loke, S.W., Krishnaswamy, S.: Generating Web Services Ratings and Reputation Rationale for Explanation-Aware Service Selection. In: Service Oriented Computing and Applications (SOCA), November 4, vol. 2, pp. 203–218. Springer, Heidelberg (2008) (to appear)
Kosala, R., Blockeel, H.: Web mining research: A survey. ACM SIGKDD Explorations Newsletter 2(1), 1–15 (2000)
Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 168–177. ACM, Seattle (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, pp. 342–351. ACM, Chiba (2005)
Popescu, A.-M., Etzioni, O.: Extracting Product Features and Opinions from Reviews. In: Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, pp. 339–346. Association for Computational Linguistics, Vancouver (2007)
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)
Scaffidi, C., Bierhoff, K., Chang, E., Felker, M., Ng, H., Jin, C.: Red Opal: product-feature scoring from reviews. In: Proceedings of the 8th ACM Conference on Electronic Commerce, pp. 182–191. ACM, San Diego (2007)
Zhao, L., Li, C.: Ontology Based Opinion Mining for Movie Reviews. In: Karagiannis, D., Jin, Z. (eds.) KSEM 2009. LNCS, vol. 5914, pp. 204–214. Springer, Heidelberg (2009)
Turney, P.: Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews. In: Proceedings of the 40th Annual Meeting of ACL, pp. 417–424. Association for Computational Linguistics, Philadelphia (2002)
Nguyen, P., Mahajan, M., Zweig, G.: Summarization of multiple user reviews in the restaurant domain,(2007), http://research.microsoft.com/apps/pubs/default.aspx?id=70488 (retrieved on February 5, 2010)
Weiss, S.M., Indurkhya, N., Zhang, T., Damerau, F.J.: Text Mining Predictive Methods for Analyzing Unstructured Information. Springer, New York (2005)
Porter, M.: The porter stemming algorithm,(2006), http://tartarus.org/~martin/PorterStemmer/ (accessed February 5, 2010)
Yoo, D., Kim, G., Suh, Y.: Hotel-Domain Ontology for a Semantic Hotel Search System. Information Technology & Tourism 11(1), 67–84 (2009)
Fellbaum, C.: WordNet: An electronic lexical database. MIT Press, Cambridge (1998)
Dekang, L.: Dependency-based evaluation of MINIPAR. In: Proceedings of the Workshop on the Evaluation of Parsing Systems, Granada, Spain, pp. 298–312 (1998)
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Rahayu, D.A.P., Krishnaswamy, S., Labbe, C., Alhakoon, O. (2010). Web Services for Analysing and Summarising Online Opinions and Reviews. In: Di Nitto, E., Yahyapour, R. (eds) Towards a Service-Based Internet. ServiceWave 2010. Lecture Notes in Computer Science, vol 6481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17694-4_12
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DOI: https://doi.org/10.1007/978-3-642-17694-4_12
Publisher Name: Springer, Berlin, Heidelberg
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