Online Product Review Monitoring System Using Machine Learning
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-90119-6_7
Reference13 articles.
1. Liang, D., Liu, X., Shen, H.: Detecting spam reviewers by combing reviewer feature and relationship. In: International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS) (2014)
2. Lin, Y., Zhu, T., Wu, H., Zhang, J., Wang, X., Zhou, A.: Towards online anti-opinion spam: spotting fake reviews from the review sequence. In: 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2014)
3. Istiaq Ahsan, M.N., Nahian, T., Kafi, A.A., Hossain, M.I., Shah, F.M.: Review spam detection using active learning. In: IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) (2016)
4. Rajamohana, S.P., Umamaheswari, K., Dharani, M., Vedackshya, R.: A survey on online review spam detection techniques. In: IEEE International Conference on Innovations in Green Energy and Healthcare Technologies (ICIGEHT’17) (2017)
5. Zhang, Q., Wu, J., Zhang, P., Long, G., Zhang, C.: Collective hyping detection system for identifying online spam activities. IEEE Intell. Syst. 32(5), September/October (2017)
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