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- Vol. 3 Issue 2
- Article
Product Review Monitoring System by Machine Learning
Authors
1Assistant Professor, Information Technology, BVCOE/Mumbai University, India. 234 B.E. Student, Information Technology, BVCOE/Mumbai University, India.
Article Information
- DOI
- No DOI
- Published In
- Volume 3, Issue 2 (2022)
- Published Online
- March-April 2022
- Pages
- 33-36
- Article Type
- Research Article
- Check for updates
- No DOI available for cross-reference
References
[1] A. Rastogi, M. Mehrotra, “Opinion spam Detection in Online Reviews”, Journal of information and Knowledge Management, vol. 16, no. 04, pp. 1-
38, 2017.
[2] J. Rout,S. Singh, S. Jena, and S. Bakshi, “Deceptive review detection using labeled and unlabelled data”, Multimedia Tools and Applications,vol.76,
no. 3, pp. 3187-3211, 2016.
[3] S. Banerjee, A. Chua, J. Kim, “Using Supervised Learning to Classify Authentic and Fake Online Reviews ”, Proceeding of the 9th International
Conference on Ubiquitous Information Management and Communication”, ACM, 2015.
[4] P.Rosso, D.Cabrera, M. Gomez, “Using PU-Learning to Detect Deceptive Opinion Spam”, pp.38-45, 2013.
[5] R.Narayan,J. Rout and S. Jena, “Review Spam Detection Using Semisupervised Technique”, Progress in Intelligent Computing Techniques: Theory,
Practice, and Applications, pp. 281-286, 2018.
[6] W. Etaiwi,G. Naymat, “The impact of applying preprocessing steps on review spam detection”, The 8th international conference on emerging
ubiquitous system and pervasion networks, Elsevier, pp. 273-279, 2017.
[7] W. Zhang,R. Y. K. Lau and Li. Chunping, “Adaptive Big Data Analytics for Deceptive Review Detection in Online Social Media”, Thirty Fifth
International Conference on Information Systems, Auckland 2014,pp.1-19,2014.
38, 2017.
[2] J. Rout,S. Singh, S. Jena, and S. Bakshi, “Deceptive review detection using labeled and unlabelled data”, Multimedia Tools and Applications,vol.76,
no. 3, pp. 3187-3211, 2016.
[3] S. Banerjee, A. Chua, J. Kim, “Using Supervised Learning to Classify Authentic and Fake Online Reviews ”, Proceeding of the 9th International
Conference on Ubiquitous Information Management and Communication”, ACM, 2015.
[4] P.Rosso, D.Cabrera, M. Gomez, “Using PU-Learning to Detect Deceptive Opinion Spam”, pp.38-45, 2013.
[5] R.Narayan,J. Rout and S. Jena, “Review Spam Detection Using Semisupervised Technique”, Progress in Intelligent Computing Techniques: Theory,
Practice, and Applications, pp. 281-286, 2018.
[6] W. Etaiwi,G. Naymat, “The impact of applying preprocessing steps on review spam detection”, The 8th international conference on emerging
ubiquitous system and pervasion networks, Elsevier, pp. 273-279, 2017.
[7] W. Zhang,R. Y. K. Lau and Li. Chunping, “Adaptive Big Data Analytics for Deceptive Review Detection in Online Social Media”, Thirty Fifth
International Conference on Information Systems, Auckland 2014,pp.1-19,2014.
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