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Detection of Fake Online Reviews using ML
2020
International Journal for Research in Applied Science and Engineering Technology
Online audits have incredible effect on the present business furthermore, trade. Basic leadership for acquisition of on the web items generally relies upon surveys given by the clients. Thus, shrewd people or gatherings attempt to control item surveys for their own advantages. This paper presents a few semi-supervised and supervised content mining models to recognize counterfeit online audits just as analyses the productivity of both procedures on dataset containing lodging surveys.
doi:10.22214/ijraset.2020.30950
fatcat:7aq4mkyq2nhyvmp54qgah6xpui