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Published in:

Volume 7 Issue 11
November-2020
eISSN: 2349-5162

Unique Identifier

JETIR2011096

Page Number

712-717

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Title

Fake Online Reviews Detection Using Semi-Supervised and Supervised Learning

ISSN

2349-5162

Cite This Article

"Fake Online Reviews Detection Using Semi-Supervised and Supervised Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 11, page no.712-717, November-2020, Available :http://www.jetir.org/papers/JETIR2011096.pdf

Abstract

Today's business and commerce is greatly impacted by Online reviews. These Online reviews are helping the users in making decisions regarding the purchase of online products. Online reviews are a great source of reputation for the companies. These reviews also have a great impact on promotion and advertisement of products and services. Hence some individuals or groups are trying to manipulate these online reviews for their own interests. This paper gives some semi-supervised and supervised text mining models to detect the fake online reviews and compares the efficiency in both the techniques on a dataset containing the reviews of some hotels.

Key Words

Fake Online reviews, Semi- supervised learning, Supervised learning, Expectation Maximization algorithm, Decision tree classifier, Naive bayes classifier, Support Vector Machine classifier.

Cite This Article

"Fake Online Reviews Detection Using Semi-Supervised and Supervised Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 11, page no. pp712-717, November-2020, Available at : http://www.jetir.org/papers/JETIR2011096.pdf

Publication Details

Published Paper ID: JETIR2011096
Registration ID: 303233
Published In: Volume 7 | Issue 11 | Year November-2020
DOI (Digital Object Identifier):
Page No: 712-717
ISSN Number: 2349-5162

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Cite This Article

"Fake Online Reviews Detection Using Semi-Supervised and Supervised Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 11, page no. pp712-717, November-2020, Available at : http://www.jetir.org/papers/JETIR2011096.pdf




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