BayesSentiRS: Bayesian sentiment analysis for addressing cold start and sparsity in ranking-based recommender systems

• Published in: Expert systems with applications Vol. 238; p. 121930
• Main Author: Wu, Liang-Hong
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.03.2024
• Subjects: Bayesian personalized ranking; Information fusion; Multi-modal sentiment fusion; Ranking-based recommendation system; Semantic sentiment analysis; Visual sentiment analysis; Ranking-based recommendation system; Semantic sentiment analysis; Multi-modal sentiment fusion; Bayesian personalized ranking; Visual sentiment analysis; Information fusion

Recommendation systems are widely used to filter massive information. However, they often face the challenges of cold start and sparsity problems, limiting their effectiveness. Bayesian Personalized Ranking (BPR), which focuses on predicting the relative order of user items, has been conventionally...