Opinion mining using principal component analysis based ensemble model for e-commerce application

G. Vinodhini1, R. Chandrasekaran1
1Department of Computer Science and Engineering, Annamalai University, Annamalai Nagar 608002, India

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Pang B, Lee L, Vaithyanathan S (2002), Thumbs up? Sentiment classification using machine learning techniques. In: Proceedings of the conference on empirical methods in natural language processing (pp 79–86)

Turney PD (2002) Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews, In: Proceedings of the 40th annual meetings of the association for computational linguistics

Abbasi A, Chen H, Salem A (2008) Sentiment analysis in multiple languages: feature selection for opinion classification in web forums. ACM Trans Inf Syst 26, 12:1–12:34

Boiy E, Moens M-F (2009) A machine learning approach to sentiment analysis in multilingual web texts. Inf Retr 12(5):526–558

Vinodhini G, Chandrasekaran RM (2012) Sentiment analysis and opinion mining: a survey. Int J Adv Res Comput Sci Softw Eng 2(6)

Pang Bo, Lee L (2004). A opinional education: Opinion analysis using subjectivity summarization based on minimum cuts. In: Proceedings 42nd ACL

Mullen T, Collier N (2004) Opinion analysis using support vector machines with diverse information sources. In: Proceedings of EMNLP-2004, Barcelona, Spain (pp 412–418)

Rushdi Saleh M, Martı´n-Valdivia MT, Montejo-Raez A, Urena-Lopez LA (2011) Experiments with SVM to classify opinions in different domains. Exper Syst Appl 38(12):14799–14804

Kim S-M, Hovy E (2004) Determining the sentiment of opinions. In: Proceedings of the 20th international conference on computational Linguistics, (Association for Computational Linguistics), p 1367

Ziqiong Zhang Z, Ye Q, Zhang Z, Li Y (2011) Sentiment classification of Internet restaurant reviews written in Cantonese. Expert Syst Appl 38(6):7674–7682

Xia Rui, Zong Chengqing, Li Shoushan (2011) Ensemble of feature sets and classification algorithms for opinion classification. Inf Sci 181:1138–1152

Li W, Wang W, Chen Y (2012) Heterogeneous ensemble learning for Chinese sentiment classification. J Inf Comput Sci 9(15):4551–4558

Tan Songho, Zhang Jin (2008) An empirical study of opinion analysis for chinese documents. Expert Syst Appl 34:2622–2629

Wang SG, Wei YJ, Zhang W, Li DY, Li W (2007) A hybrid method of feature selection for chinese text opinion classification [C]. In: Proceedings of the 4th international conference on fuzzy systems and knowledge discovery (pp 435–439). IEEE Computer Society

Liu B (2010) Sentiment analysis and subjectivity. Handb Nat Lang Process, pp 627–666

Pang B, Lee L (2008) Opinion mining and sentiment analysis. Found Trends Inf Retr 2(1–2):1–135

Tang H, Tan S, Cheng X (2009) A survey on sentiment detection of reviews. Expert Syst Appl 36(7):10760–10773

Tsytsarau M, Palpanas T (2011) Survey on mining subjective data on the web. Data Min Knowl Discov 24:1–37

Li S, Xia R, Zong C, Huang C-R (2009) A framework of feature selection methods for text categorization. In: Proceedings of the 47th annual meeting of the ACL (pp 692–700)

Melville, Wojciech Gryc, “Opinion Analysis of Blogs by Combining Lexical Knowledge with Text Classification”, KDD’09, June 28–July 1, 2009, Paris, France. Copyright 2009 ACM 978-1-60558-495-9/09/06

Prabowo R, Mike T Barcelona, Spain (2009) Opinion analysis: a combined approach. J Inf 3:143–157

Wang S, Deyu L, Yingjie W, Hongxia L (2009) “A feature selection method based on fisher’s discriminant ratio for text sentiment classification.” In: Web information systems and mining. Springer, Berlin, Heidelberg, pp 88–97

Abbasi A, France S, Zhang Z, Chen H (2011) Selecting attributes for sentiment classification using feature relation networks. IEEE Trans Knowl Data Eng 23:447–462

Chen L-S, Liu C-H, Chiu H (2011) A neural network based approach for sentiment classification in the blogosphere. J Informetr 5:313–322

Cambria E, Schuller B, Xia Y, Havasi C (2013) “New avenues in opinion mining and sentiment analysis.” IEEE Intell Syst 28(2):15–21

Tsytsarau M, Palpanas, T (2012) Survey on mining subjective data on the web. Data Min Knowl Discov 24(3):478–514

Chen JS (2003) Market segmentation by tourists’ sentiments. Ann Tour Res 30(1):178–193

Whitehead M, Yaeger L (2010) “Sentiment mining using ensemble classification models.” In: Innovations and advances in computer sciences and engineering, Springer, Netherlands, 509–514

Vinodhini G, Chandrasekaran RM (2013) Effect of feature reduction in sentiment analysis of online reviews. Int J Adv Res Comput Eng Technol (IJARCET) 2(6):2165–2172

Sista S, Srinivasan S, (2004) Polarized lexicon for review classification. In: Proceedings of the international conference on machine learning; models, technologies and applications 2004

Cho YH, Lee KJ (2006) Automatic affect recognition using natural language processing techniques and manually built affect lexicon. IEICE Tran Inf Syst E89(12):2964–2971

Gamon M (2004) Sentiment classification on customer feedback data: noisy data, large feature vectors, and the role of linguistic analysis. In: Proceeding of the 20th intl. conference on computational linguistics (p 84)

O’Keefe T, Koprinska I (2009) Feature selection and weighting methods in sentiment analysis, In: Proceedings of the Australasian document computing symposium (pp 67–74)

Dave K, Lawrence S, Pennock D (2003) Mining the peanut gallery: opinion extraction and semantic classification of product reviews. In Proceeding of 12th intl. conference on the WWW, (pp 519–528)

Chen H (2006) Intelligence and security informatics: information systems perspective. Decis Support Syst 41(3):555–559

Chau M, Xu J (2007) Mining communities and their relationships in blogs: a study of online hate groups. Int J Hum-Comput Stud 65(1):57–70

Raghu TS, Chen H (2007) Cyberinfrastructure for homeland security: advances in information sharing, data mining, and collaboration systems. Decis Support Syst 43(4):1321–1323

Briand L, Daly J, Wust J (2000) A unified framework for coupling measurement in object-oriented systems. IEEE Trans Softw Eng 25(1):91–121

Kennedy A, Inkpen D (2006) Opinion classification of movie reviews using contextual valence shifters. Comput Intell 22(2):110–125

Gamon M, Aue A (2005) Automatic identification of sentiment vocabulary: exploiting low association with known sentiment terms. In: Proceedings of the ACL workshop on feature engineering for machine learning in natural language processing. Association for Computational Linguistics, pp 57–64

Salvetti F, Lewis S, Reichenbach C (2004) Automatic opinion polarity classification of movie reviews. Colorado research in linguistics. University of Colorado, Boulder (vol. 17, no. 1)

Whitelaw C, Garg N, Argamon S (2005) Using appraisal groups for opinion analysis. In: Proceedings of CIKM-05, 14th ACM international conference on information and knowledge management, Bremen (pp 625–631)

Beineke P, Trevor H, Shivakumar V (2004) “The sentimental factor: improving review classification via human-provided information.” In: Proceedings of the 42nd annual meeting on association for computational linguistics. Association for Computational Linguistics

Whitehead M, Yaeger L (2008) Opinion mining using ensemble classification models. In: International conference on systems, computing sciences and software engineering (SCSS 08), Springer, Berlin