A review of feature selection techniques in sentiment analysis-Reference-Cited by-同舟云学术

A review of feature selection techniques in sentiment analysis

Published:2019-02-20 Issue:1 Volume:23 Page:159-189
ISSN:1088-467X
Container-title:Intelligent Data Analysis
language:
Short-container-title:IDA

Author:

Ahmad Siti Rohaidah¹,Bakar Azuraliza Abu²,Yaakub Mohd Ridzwan²

Affiliation:

1. Department of Computer Science, Faculty of Defence Science and Technology, Universiti Pertahanan Nasional Malaysia, Kuala Lumpur, Malaysia

2. Data Mining and Optimization Research Group, Centre for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Selangor, Malaysia

Publisher

IOS Press

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Theoretical Computer Science

Reference97 articles.

1. Care more about customers: Unsupervised domain-independent aspect detection for sentiment analysis of customer reviews;Bagheri;Knowledge-Based Systems,2013

2. Z. Zhai, B. Liu, H. Xu and J. Peifa, Constrained LDA for Grouping Product Features in Opinion Mining, in: J. Huang, L. Cao, J. Srivastava (Eds.), Proceedings of the 15th Pacific-Asia Conference on Advances in Knowledge Ddscovery and Data Mining, Springer, 2011, pp. 448–459. http://www.springerlink.com/index/Q73120K14T206727.pdf.

3. Opinion mining and sentiment analysis;Pang;Foundations and Trends® in Information Retrieval,2008

4. K. Khan, B.B. Baharudin, A. Khan and F. e-Malik, Mining opinion from text documents: A survey, in: 2009 3rd IEEE International Conference on Digital Ecosystems and Technologies, 2009.

5. Sentiment analysis and opinion mining: A survey;Vinodhini;International Journal of Advanced Research in Computer Science and Software Engineering,2012

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