Online recommender system for radio station hosting based on information fusion and adaptive tag-aware profiling
作者：
Highlights：
• A new implicit feedback recommender system for the interactive radio network FMhost.
• A collaborative approach paired with dynamic tag-aware profiles or users and radios.
• An adaptive online learning strategy based on user history and information fusion.
• We compare it with an SVD-based technique in terms of precision, recall, and NDCG.
• Our experiments show that the fusion-based approach demonstrates the best results.
摘要
•A new implicit feedback recommender system for the interactive radio network FMhost.•A collaborative approach paired with dynamic tag-aware profiles or users and radios.•An adaptive online learning strategy based on user history and information fusion.•We compare it with an SVD-based technique in terms of precision, recall, and NDCG.•Our experiments show that the fusion-based approach demonstrates the best results.
论文关键词：Music recommender system,Interactive radio network,Hybrid recommender system,Information fusion,Adaptive tag-aware profiling,Implicit feedback
论文评审过程：Received 22 July 2014, Revised 13 February 2016, Accepted 14 February 2016, Available online 18 February 2016, Version of Record 14 March 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.02.020
