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Analyzing Product Reviews and Predicting Sentiments using Fuzzy Classifier

Rupali P. Jondhale, Manisha P. Mali

Abstract


Sentiment Analysis become a challenge in promising field like data mining. It analyses sentiment, attitude, emotion and opinion of people who had commented about service or purchased product on different e-commerce sites. Comments or reviews given online consist of information in unstructured, vague manner. Efficient way is needed to analyze and classify such electronic content for predicting sentiments about particular product. For extracting meaningful words pre-processing of unstructured text is important. This paper suggest an enhanced methodology along with preprocessing technique. Method includes analysis of product reviews using ontology and fuzzy classifier.

Keywords


Fuzzy Classifier, Natural language Processing (Preprocessing), Ontology, Sentiment Analysis.

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References


Janyce Wiebe and Ellen Riloff, "Finding Mutual Benefit between Subjectivity Analysis and Information Extraction", IEEE Transactions on Affective Computing, October-December 2011.

Xiaohui Yu, Yang Liu, Jimmy Xiangji Huang and Aijun An, "Mining Online Reviews for Predicting Sales Performance: A Case Study in the Movie Domain", IEEE Transactions on Knowledge and Data engineering, April 2012.

Chenghua Lin, Yulan He, Richard Everson, Member and Stefan Ruger, "Weakly Supervised Joint Sentiment-Topic Detection from Text", IEEE Transactions on Knowledge and Data engineering, June 2012.

Yan Dang, Yulei Zhang, and Hsinchun Chen,"A Lexicon-Enhanced Method for Sentiment Classification: An Experiment on Online Product Reviews", IEEE Computer Society Intelligent Systems, 1541-1672, 2010.

Jayashri Khairnar, Mayura Kinikar, "Machine Learning Algorithms for Opinion Mining and Sentiment Classification", International Journal of Scientific and Research Publications, June 2013.

XU Xueke, CHENG Xueqi, TAN Songbo, LIU Yue, SHEN Huawei, "Aspect-Level Opinion Mining of Online Customer Reviews", China Communications on Management and visualization of user and network data, March 2013.

Danushka Bollegala, Member, David Weir, and John Carroll, "Cross-Domain Sentiment Classification Using a Sentiment Sensitive Thesaurus", IEEE Transactions on Knowledge and Data engineering, August 2013.

Efstratios Kontopoulos, Christos Berberidis, Theologos Dergiades, Nick Bassiliades, "Ontology-based sentiment analysis of twitter posts", IEEE Transactions on Expert Systems with Applications 40, 4065–4074, 2013.

Isidro Peñalver-Martinez a, Francisco Garcia-Sanchez, “Feature-based opinion mining through ontologies”, IEEE Transactions on Expert Systems with Applications, 2014.

V. Ramkumar, S. Rajasekar, S. Swamynathan, "Scoring products from reviews through application of fuzzy techniques", IEEE Transactions on Expert Systems with Applications 37, 6862–6867, 2010.

N.L.BHALE, "A fuzzy approach for sentiment analysis based on web customer reviews", Proceedings of 11th IRF International Conference, June-2014.

Santanu Modak, Abhoy Chand Mondal, "A Study on Sentiment Analysis", International Journal of Advanced Research in Computer Science & Technology (IJARCST) 284 Vol. 2, Issue 2, Ver. 2 , April - June 2014.

Bo Pang and Lillian Lee, Shivakumar Vaithyanathan, “Thumbs up Sentiment Classification using Machine Learning Techniques”, Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Philadelphia, July 2013.

Erik Cambria, Björn Schuller, Yunqing Xia, Catherine Havasi, "New Avenues in Opinion Mining and Sentiment Analysis", IEEE Computer Society, 1541-1672, March/April 2013.

Nayana Mariya Varghese and Jomina John, “ Cluster ptimization for Enhanced Web Usage Mining using Fuzzy Logic”, IEEE World congress on Information and Communication Technologies, pp.948-952, 2012.

G.Vinodhini, RM.Chandrasekaran , " Sentiment Analysis and Opinion Mining: A Survey ", International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 6, June 2012.

Sumeet V. Vinchurkar, Smita M. Nirkhi, "Extracting the opinion through customer feedback data from web resources", International Journal of Research in Engineering & Applied Sciences, Volume 2, Issue 2 , February 2012.

Daniel Tao, Yuefeng Li, Ning Zhong, “A personalized ontology model for web information gathering,” IEEE Transactions on Knowledge and Data Engineering 23 (4) 496–511, April 2011.

S. Baccianella, A. Esuli, F. Sebastiani, "Sentiwordnet 3.0: an enhanced lexical resource for sentiment analysis and opinion mining", Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC’10), 2010.

Bo Pang and Lillian Lee, "Opinion Mining and Sentiment Analysis", IEEE Transactions on Foundations and Trends in Information Retrieval Vol. 2, 1––135, 2008.

Ding X., Liu B., and Philip Y., “A Holistic Lexicon-Based Approach to

Opinion Mining,” , Proc. Int. Conf. Web Search Web Data Mining, , pp. 231- 240, 2008.

Samaneh N., Masrah A. Murad, Rabiah, Abdul Kadir, "Sentiment Classification of Customer Reviews Based on Fuzzy Logic", Information Technology (ITSim), International Symposium, pp. 1037-1040, 2010.

Ak. Kumar and T. M. Sebastian.," Sentiment Analysis: A Perspective on ItsPast, Present and Future", International Journal of Intelligent Systems and Applications, 4(10):1-14, 2012.

Cambria E, Schuller B, Xia Y, Havasi C., " New avenues in opinion mining and sentiment analysis", IEEE Transaction on Intelligent System; 28:15–21, 2013.


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