Unbiasing Review Ratings with Tendency Based Collaborative Filtering
2020-12-01Asian Chapter of the Association for Computational LinguisticsCode Available0· sign in to hype
Pranshi Yadav, Priya Yadav, Pegah Nokhiz, Vivek Gupta
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Abstract
User-generated contents' score-based prediction and item recommendation has become an inseparable part of the online recommendation systems. The ratings allow people to express their opinions and may affect the market value of items and consumer confidence in e-commerce decisions. A major problem with the models designed for user review prediction is that they unknowingly neglect the rating bias occurring due to personal user bias preferences. We propose a tendency-based approach that models the user and item tendency for score prediction along with text review analysis with respect to ratings.