RecomMetz: A context-aware knowledge-based mobile recommender system for movie showtimes

作者：

Highlights：

• A novel semantic-based recommender system in the leisure domain is proposed.

• The context-aware approach is based on location, time and crowd information.

• Recommended items are viewed as composed items: movie theater + movie + showtime.

• Good performance results were obtained under cold-start real world scenarios.

摘要

•A novel semantic-based recommender system in the leisure domain is proposed.•The context-aware approach is based on location, time and crowd information.•Recommended items are viewed as composed items: movie theater + movie + showtime.•Good performance results were obtained under cold-start real world scenarios.

论文关键词：Knowledge-based recommender systems,Context-aware systems,Semantic Web,Ontology reasoning

论文评审过程：Available online 22 September 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.09.016