UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 4
April-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR2304C25


Registration ID:
514165

Page Number

m225-m229

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Title

Partially Supervised Learning Group Detection

Abstract

With the continual evolution of E-commerce platforms, online evaluations are increasingly seen as a critical aspect in establishing and maintaining a positive reputation. Furthermore, they play an important role in the decision-making process for end users. A positive review for a specific object typically draws more customers and leads to a significant rise in sales. Deceptive or phony evaluations are now purposefully generated in order to build a virtual reputation and attract potential clients. As a result, detecting false reviews is an active and ongoing research topic. Identifying phony reviews is dependent not only on the essential elements of the reviews, but also on the reviewers' behaviour. This research provides a machine learning method for detecting false reviews. In addition to the review features extraction approach, this research employs different features engineering techniques to extract diverse reviewer behaviours. The study examines the performance of machine learning classifiers; KNN, Naive Bayes, and Logistic Regression using a genuine Yelp dataset of restaurant reviews. In terms of accuracy, the results show that Logistic Regression surpasses the other classifiers. The results demonstrate that the system is better at determining whether a review is fake or genuine.

Key Words

Machine learning, fake, reviews, Naive Bayes, KNN, Logistic Regression

Cite This Article

"Partially Supervised Learning Group Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 4, page no.m225-m229, April-2023, Available :http://www.jetir.org/papers/JETIR2304C25.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Partially Supervised Learning Group Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 4, page no. ppm225-m229, April-2023, Available at : http://www.jetir.org/papers/JETIR2304C25.pdf

Publication Details

Published Paper ID: JETIR2304C25
Registration ID: 514165
Published In: Volume 10 | Issue 4 | Year April-2023
DOI (Digital Object Identifier):
Page No: m225-m229
Country: LUCKNOW, Uttar Pradesh, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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