Fine Grained Opinion Mining from Online Reviews for Product Recommendation

Authors(2) :-Rahul S. Gaikwad, Dr. B. L. Gunjal

Fine grained opinion mining is an important task in today’s E-business world. Customers and manufacturers wanted to know about products in details. So in this paper we have studied opinion targets and opinion word extraction through dependency parsing and by applying syntactic patterns. Previously developed double propagation approach is useful for extraction task with addition of some syntactic relations. Also finding opinion orientation can be performed using dictionary and some contrary words, conjunctions. We can also generate a summary to analysis and recommendations. By using opinion target list and opinion word lexicon we can achieve better results.

Authors and Affiliations

Rahul S. Gaikwad
Department of Computer Engineering, Amrutvahini College of Engineering, Sangamner, Maharashtra, India
Dr. B. L. Gunjal
Department of Computer Engineering, Amrutvahini College of Engineering, Sangamner, Maharashtra, India

Opinion target, Opinion words, Opinion orientation, Recommendation.

  1. S. M. K. Liu, L. Xu, and J. Zhao, “Co-Extracting Opinion Targets and Opinion Words from Online  Reviews Based on the Word Alignment Model” in IEEE Transactions on Knowledge and Data Engineering, Vol. 27, no. 3, pp.636-650, March 2015.
  2. M. Hu and B. Liu, “Mining and summarizing customer reviews,” in Proc. 10th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, Seattle, WA, USA, pp. 168–177, 2004.
  3. F. Li, S. J. Pan, O. Jin, Q. Yang, and X. Zhu, “Cross-domain co-extraction of sentiment and topic lexicons,” in Proc. 50th Annu. Meeting Assoc. Comput. Linguistics, Jeju, Korea, pp. 410-419, 2012.
  4. L. Zhang, B. Liu, S. H. Lim, and E. O’Brien-Strain, “Extracting and ranking product features in opinion documents,” in Proc. 23th Int. Conf. Comput. Linguistics, Beijing, China, pp. 1462–1470, 2010.
  5. K. Liu, L. Xu, and J. Zhao, “Opinion target extraction using word based translation model,” in Proc. Joint Conf. Empirical Methods Natural Lang. Process. Comput. Natural Lang. Learn., Jeju, Korea, pp. 1346–1356, Jul. 2012.
  6. M. Hu and B. Liu, “Mining opinion features in customer reviews,” in Proc. 19th Nat. Conf. Artif. Intell., San Jose, CA, USA, pp. 755–760, 2004.
  7. A.-M. Popescu and O. Etzioni, “Extracting product features and opinions from reviews,” in Proc. Conf. Human Lang. Technol. Empirical Methods Natural Lang. Process., Vancouver, BC, Canada, pp. 339–346, 2005.
  8. G. Qiu, L. Bing, J. Bu, and C. Chen, “Opinion word expansion and target extraction through double propagation,” Comput. Linguistics, vol. 37, no. 1, pp. 9–27, 2011.
  9. B. Wang and H. Wang, “Bootstrapping both product features and opinion words from chinese customer reviews with crossinducing,” in Proc. 3rd Int. Joint Conf. Natural Lang. Process., Hyderabad, India, pp. 289–295, 2008.
  10. B. Liu, Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data, series Data-Centric Systems and Applications. New York, NY, USA: Springer, 2007.
  11. G. Qiu, B. Liu, J. Bu, and C. Che, “Expanding domain sentiment lexicon through double propagation,” in Proc. 21st Int. Jont Conf. Artif. Intell., Pasadena, CA, USA, pp. 1199–1204, 2009.
  12. R. C. Moore, “A discriminative framework for bilingual word alignment,” in Proc. Conf. Human Lang. Technol. Empirical Methods Natural Lang. Process., Vancouver, BC, Canada, pp. 81–88, 2005.
  13. X. Ding, B. Liu, and P. S. Yu, “A holistic lexicon-based approach to opinion mining,” in Proc. Conf. Web Search Web Data Mining, pp. 231–240, 2008.
  14. F. Li, C. Han, M. Huang, X. Zhu, Y. Xia, S. Zhang, and H. Yu, “Structure-aware review mining and summarization.” in Proc. 23th Int. Conf. Comput. Linguistics, Beijing, China, pp. 653–661, 2010.
  15. Y. Wu, Q. Zhang, X. Huang, and L. Wu, “Phrase dependency parsing for opinion mining,” in Proc. Conf. Empirical Methods Natural Lang. Process., Singapore, pp. 1533–1541, 2009.
  16. T. Ma and X. Wan, “Opinion target extraction in chinese news comments.” in Proc. 23th Int. Conf. Comput. Linguistics, Beijing, China, pp. 782–790, 2010.
  17. Q. Zhang, Y. Wu, T. Li, M. Ogihara, J. Johnson, and X. Huang, “Mining product reviews based on shallow dependency parsing,” in Proc. 32nd Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, Boston, MA, USA, pp. 726–727, 2009.
  18. W. Jin and H. H. Huang, “A novel lexicalized HMM-based learning framework for web opinion mining,” in Proc. Int. Conf. Mach. Learn., Montreal, QC, Canada, pp. 465–472, 2009.
  19.  S. Meng, W. Dou, X. Zhang, J. Chen, KASR: A Keyword-Aware Service Recommendation Method on MapReduce for Big Data ApplicationsIEEE Transactions On Parallel And Distributed Systems, Tpds-2013-12-1141, pp. 1-11, 2013.

Publication Details

Published in : Volume 2 | Issue 3 | May-June 2016
Date of Publication : 2016-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 410-416
Manuscript Number : IJSRSET1623127
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Rahul S. Gaikwad, Dr. B. L. Gunjal, " Fine Grained Opinion Mining from Online Reviews for Product Recommendation, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 3, pp.410-416, May-June-2016.
Journal URL : http://ijsrset.com/IJSRSET1623127

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