Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Reference :

    1. Zhi-Hong Deng , Kun-Hu Luo and Hong-Liang Yu(2014), “A study of supervised term weighting scheme for sentiment analysis”, Elsevier, Expert Systems with Applications ,Vol.41(7),PP. 3506–3513.
    2. Alvaro Ortigosa, José M. Martín and Rosa M. Carro(2014),” Sentiment analysis in Facebook and its application to e-learning”, Elsevier,Computers in Human Behavior ,Vol.31, PP.527–541.
    3. Li.T.,Zhu.S., &Ogihara.M. (2008), “Text ategorization via generalized discriminant analysis”, Information Processing & Management, 44(5), 1684-1697. 167
    4. Liang. J., Liu. P., Tan. J., & Bai. S. (2014), “Sentiment Classification Based on AS-LDA Model”, Procedia Computer Science, 31, 511-516.
    5. Liu.B.,&Zhang.L. (2012), “A survey of opinion mining and sentiment analysis”, In Mining Text Data, Springer US, 415- 463.
    6. Miao. Q., Li. Q., & Zeng. D. (2010), “Mining fine grained opinions by using probabilistic models and domain knowledge”, Proceedings of the 2010 IEEE/ WIC/ACM international conference on web intelligence and intelligent agent technology – WI-IAT’10 ,Washington, DC, USA: IEEE Computer Society 01, 358–365,.
    7. Min-Chul Yang and Hae-Chang Rim(2014), “Identifying interesting Twitter contents using topical analysis”, Expert Systems with Applications ,Elsevier,Vol.41(9),PP. 4330–4336
    8. Moraes. R., Valiati. J. F. &GaviãONeto. W. P. (2013), “Document-level sentiment classification: An empirical comparison between SVM and ANN”, Expert Systems with Applications, 40(2), 621-633.
    9. Nasukawa. T., & Yi. J. (2003), “Sentiment analysis: Capturing favorability using natural language processing”, In Proceedings of the 2nd international conference on Knowledge capture, ACM, 70-77.
    10. Xia.R.,Zong.C., Hu.X., &Cambria.E. (2013), “Feature ensemble plus sample selection: domain adaptation for sentiment classification”, Intelligent Systems, IEEE, 28(3), 10-18.

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