A hybrid context-aware approach for e-tourism package recommendation based on asymmetric similarity measurement and sequential pattern mining
作者：
Highlights：
• Integrating four different methods to improve the quality of the recommendations.
• A dynamic approach to incorporate context information into the recommendation process.
• Proposing an asymmetric score function in order to improve the accuracy of prediction.
• Suggesting dynamic travel recommendation based on current context information implicitly.
• Applying the personalized PoIs to the sequential travel patterns for each user.
摘要
•Integrating four different methods to improve the quality of the recommendations.•A dynamic approach to incorporate context information into the recommendation process.•Proposing an asymmetric score function in order to improve the accuracy of prediction.•Suggesting dynamic travel recommendation based on current context information implicitly.•Applying the personalized PoIs to the sequential travel patterns for each user.
论文关键词：Travel package recommendation,Tourism,Collaborative filtering,Context-awareness,Demographic,Sequential pattern mining
论文评审过程：Received 27 July 2019, Revised 7 February 2020, Accepted 20 April 2020, Available online 22 April 2020, Version of Record 17 June 2020.
论文官网地址：https://doi.org/10.1016/j.elerap.2020.100978
