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Research Article
A Survey on Fake Customer Review Detection System
Abhishek Kumar Roy1
Devsharan Singh2
Imran Raeeni3
Izmamul Ansari4
Vijendra Pratap Singh5
1234 B. Tech Student, Computer Science and Engineering, Institute of Technology and Management, Gorakhpur, U.P., India. 5 Assistant Professor, Computer Science and Engineering, Institute of Technology and Management, Gorakhpur,U.P., India.
Published Online: November-December 2022
Pages: 53-55
Cite this article
No DOIReferences
[1] Estimating the incidence of fraud in online review communities: Ott M., Cardie, C., Hancock, J. 201210 is found in the book Proceedings
of the 21st International World Wide Web Conference. ACM (2012)
[2] Anonymity, social image, and volunteer recruitment: a case study of the internet market for reviews, Wang, Z. B.E. Journal of Economic
Analysis, 10(1), 133 (2010)
[3] Ott, M., Choi, Y., Cardie, and J.T. Hancock: Finding misleading opinion spam by whatever means necessary. In: Human Language
Technologies, Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, Portland, Oregon, USA, pp. 309319
(2011)
[4] Time series-based fake opinion detection by Heydari, Tavakoli, and Salim. 58, 8392 Expert Syst. Appl (2016) Using rating behaviours,
Lim, E.-P., Nguyen, V.-A., Jindal, N., Liu, B., and Lauw, H.W., were able to identify spammy product reviews. 19th ACM International
Conference on Information Proceedings.
[5] Xie, S., Wang, G., Lin, S., Yu, P.S.: Review spam detection via temporal pattern discovery. In: Proceedings of the 18th ACM
International Conference on Knowledge Discovery and Data Mining, pp. 823831. ACM (2012)
[6] Ye, J., Kumar, S., Akoglu, L.: Temporal opinion spam detection by multivariate indicative signals. In: ICWSM, pp. 743746 (2016)
[7]. Damien Rolon-Merette, Matt Ross, Thadde Rolon-Merette, Kinsey Church, “INTRODUCTION TO ANACONDA AND PYTHON:
INSTALLATION AND SETUP”, Volume:16/Issues:05/2020.
[8]. Stefan van der Walt, S. Chris Colbert, Gael Varoquaux, “THE NUMPY ARRAY: A STRUCTURE FOR EFFICIENT NUMERICAL
COMPUTION” 8 Feb-2011.
of the 21st International World Wide Web Conference. ACM (2012)
[2] Anonymity, social image, and volunteer recruitment: a case study of the internet market for reviews, Wang, Z. B.E. Journal of Economic
Analysis, 10(1), 133 (2010)
[3] Ott, M., Choi, Y., Cardie, and J.T. Hancock: Finding misleading opinion spam by whatever means necessary. In: Human Language
Technologies, Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, Portland, Oregon, USA, pp. 309319
(2011)
[4] Time series-based fake opinion detection by Heydari, Tavakoli, and Salim. 58, 8392 Expert Syst. Appl (2016) Using rating behaviours,
Lim, E.-P., Nguyen, V.-A., Jindal, N., Liu, B., and Lauw, H.W., were able to identify spammy product reviews. 19th ACM International
Conference on Information Proceedings.
[5] Xie, S., Wang, G., Lin, S., Yu, P.S.: Review spam detection via temporal pattern discovery. In: Proceedings of the 18th ACM
International Conference on Knowledge Discovery and Data Mining, pp. 823831. ACM (2012)
[6] Ye, J., Kumar, S., Akoglu, L.: Temporal opinion spam detection by multivariate indicative signals. In: ICWSM, pp. 743746 (2016)
[7]. Damien Rolon-Merette, Matt Ross, Thadde Rolon-Merette, Kinsey Church, “INTRODUCTION TO ANACONDA AND PYTHON:
INSTALLATION AND SETUP”, Volume:16/Issues:05/2020.
[8]. Stefan van der Walt, S. Chris Colbert, Gael Varoquaux, “THE NUMPY ARRAY: A STRUCTURE FOR EFFICIENT NUMERICAL
COMPUTION” 8 Feb-2011.
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