A Systematic Study on Fake Review Detection Approaches on E-Commerce Platforms
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-58604-0_25
Reference17 articles.
1. Salminen, J., Kandpal, C., Kamel, A.M., Jung, S.G., Jansen, B.J.: Creating and detecting fake reviews of online products. J. Retail. Consum. Serv. 64, 102771 (2022)
2. Sree, V.S., Logu, K.: A novel semi-supervised algorithm to find accuracy in fake review detection using comparing with K-neighbours algorithm. In: 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), pp. 647–651. IEEE, December 2022
3. Kashti, M.R.P., Prasad, P.S.: Enhancing NLP techniques for fake review detection. Int. Res. J. Eng. Technol. (IRJET) 6, 241–245 (2019)
4. Devika, P., Veena, A., Srilakshmi, E., Reddy, A.R., Praveen, E.: Detection of fake reviews using NLP & Sentiment Analysis. In: 2021 6th International Conference on Communication and Electronics Systems (ICCES), pp. 1534–1537. IEEE, July 2021
5. Furia, R., Gaikwad, K., Mandalya, K., Godbole, A.: Tool for review analysis of product. In: 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE), pp. 1–6. IEEE, February 2020
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