Evaluation of AI Techniques for Detecting Deceptive Reviews in Cyberspace: A Study of Pre- and Post-COVID-19 Trends-Reference-Cited by-同舟云学术

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Evaluation of AI Techniques for Detecting Deceptive Reviews in Cyberspace: A Study of Pre- and Post-COVID-19 Trends

Published:2023-03-02 Issue: Volume: Page:
ISSN:
Container-title:2023 Second International Conference on Electronics and Renewable Systems (ICEARS)
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Author:

Samineni Lavanya¹,Peddi Anudeep²,Kasukurthi Aravindha¹,Rao M.V.P. Chandra Sekhara¹,Niharika Gokavarapu¹,Chereddy Sai Vignesh³

Affiliation:

1. RVR & JC College Of Engineering,Department of Computer Science and Business Systems,Guntur,India

2. RVR & JC College Of Engineering,Department of Computer Science (Data Science),Guntur,India

3. RVR & JC College Of Engineering,Department of Computer Science,Guntur,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10084918/10084923/10085689.pdf?arnumber=10085689

Reference36 articles.

1. Unfair Reviews Detection on Amazon Reviews using Sentiment Analysis with Supervised Learning Techniques

2. Internal Emotion Classification Using EEG Signal With Sparse Discriminative Ensemble

3. Robust detection of comment spam using entropy rate

4. Application of EOS-ELM With Binary Jaya-Based Feature Selection to Real-Time Transient Stability Assessment Using PMU Data

5. The WEKA data mining software

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