Employing Semi-Supervised and Supervised Learning to Discover False Online Ratings
Journal Title: International Journal of Innovative Research in Computer Science and Technology - Year 2023, Vol 11, Issue 3
Abstract
Today's modern industry and trade, internet evaluations matter a lot. Buying web items is often influenced by the opinions of other customers. Because of this, unscrupulous folks or organisations attempt to rig customer evaluations to their personal advantage. Using a lodging rating database, this research examines the performance of semi-supervised (SSVD) and supervised (SVD) word extraction methods for detecting false ratings.
Authors and Affiliations
Giribabu Sadineni, Janardhan Reddy D, Ch. Meghana Sri, K. Deepthi, M. Kaveri, J. Aiswarya
Keywords
Related Articles
- EP ID EP745156
- DOI 10.55524/ijircst.2023.11.3.18
- Views 3
- Downloads 0
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