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Fake Review Detection

Saurav Waghmare, Tushar Shinde, Susheel Daware, Shraddha Subhedar

Abstract


In the enterprise marketing process, online information assumes progressively significant job. As a kind of information, counterfeit surveys of the items, have been genuinely influencing the unwavering quality of both dynamic and information examination of the undertaking. To distinguish spam surveys, the paper presents a lot of conclusion spam discovery's ID markers dependent on conduct highlights of the spammer. Our review identification algorithm achieves lower latency. More importantly, the proposed algorithm for recognizing honest reviews can be used to analyze the relevancy between the review content and the given review topic by using the word segmentation technique. The Experimental results show that the number of fake reviews by our algorithms is higher than that of the traditional algorithm.

Keywords: Word Segmentation, Spam reviews, Stemming, technology, fake detection

Cite this Article: Saurav Waghmare, Tushar Shinde, Susheel Daware, Shraddha Subhedar. Fake Review Detection. Journal of Operating Systems Development & Trends. 2020; 7(2): 6–13p.


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DOI: http://dx.doi.org/10.37591%2Fjoosdt.v7i2.2562

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