A Fake Review Detection: A Machine Learning-Based Approach
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A Fake Review Detection: A Machine Learning-Based Approach
Authors:
Prof.T.Kiruba Rani
Assistant Professor
Department of Computer Science
Sri Krishna Arts and Science College, Coimbatore.
Kavin Raaj S
Sri Krishna Arts and Science College, Coimbatore.
ABSTRACT: Fake reviews pose a significant challenge in e-commerce and online services, misleading consumers and damaging business reputations. This study introduces a machine learning-based approach to detect fraudulent reviews, leveraging Natural Language Processing (NLP) techniques and deep learning models. By analyzing textual patterns, sentiment, and reviewer behavior, the system classifies reviews as genuine or fake. The proposed solution enhances the reliability of online reviews, promoting transparency and trust among users. The model is trained on a dataset of real and fake reviews to improve accuracy. Various evaluation metrics are used to assess the system’s performance. This approach helps businesses and consumers make informed decisions based on authentic feedback.
KEYWORDS: Fake review detection, machine learning, NLP, sentiment analysis, deep learning, fraud detection.
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