Recommendation quality
How relevant, useful, and satisfying a system's recommendations are.
9 papers carry this theme
In these papers
- 01A personalized product recommendation model in e-commerce based on retrieval strategyNguyen · 2024Improves the recommendation engine's relevance.
- 02Service-Aware Personalized Item RecommendationReceived February · 2022Adds extrinsic service factors to improve rating estimates.
- 03A tale of two recommender systems: The moderating role of consumer expertise on artificial intelligence based product recommendationsPipat Thontirawong b, Punjaporn Chinchanachokchai c · 2021Tests acceptance of AI product recommendations.
- 04Interactive Music Genre Exploration with Visualization and Mood ControlYu Liang · 2021Supports acceptance and exploration of new tastes.
- 05An Effective Clustering‑Based Web Page Recommendation Framework for E‑Commerce WebsitesHarpreet Singh · 2020Targets the gap where few visits lead to purchase.
- 06Artificial intelligence in recommender systemsZhang · 2020Learns from past behaviour to improve recommendations.
- 07User Preferences for Hybrid ExplanationsPigi Kouki · 2017Hybrid sources improve accuracy over single-source strategies.
- 08Deep Neural Networks for YouTube RecommendationsPaul Covington, Jay Adams et al. · 2016Deep learning brings dramatic recommendation improvements.
- 09Machine Learning Techniques for Recommender Systems – A Comparative Case AnalysisBinu Thomas · 2011Seeks the best algorithm for accurate recommendations.