An extensive study on the evolution of context-aware personalized travel recommender systems

作者：

Highlights：

• Explicitly focusing on recommender systems in travel and tourism domain.

• Covers evolution of travel recommender systems and their features.

• Discusses key algorithms for classification and recommendation processes.

• Describes performance metrics for prediction, recommendation and ranking.

摘要

•Explicitly focusing on recommender systems in travel and tourism domain.•Covers evolution of travel recommender systems and their features.•Discusses key algorithms for classification and recommendation processes.•Describes performance metrics for prediction, recommendation and ranking.

论文关键词：Recommender system,Personalization,Context aware,Big data,Travel and tourism

论文评审过程：Received 4 January 2019, Revised 27 April 2019, Accepted 4 July 2019, Available online 11 July 2019, Version of Record 11 November 2019.

论文官网地址：https://doi.org/10.1016/j.ipm.2019.102078