Personalized Travel Package with Multi-Point-of-Interest Recommendation Based on Crowdsourced User Footprints

Zhiwen Yu, Huang Xu, Zhe Yang, Bin Guo

科研成果: 期刊稿件文章同行评审

219 引用 (Scopus)

摘要

Location-based social networks (LBSNs) provide people with an interface to share their locations and write reviews about interesting places of attraction. The shared locations form the crowdsourced digital footprints, in which each user has many connections to many locations, indicating user preference to locations. In this paper, we propose an approach for personalized travel package recommendation to help users make travel plans. The approach utilizes data collected from LBSNs to model users and locations, and it determines users' preferred destinations using collaborative filtering approaches. Recommendations are generated by jointly considering user preference and spatiotemporal constraints. A heuristic search-based travel route planning algorithm was designed to generate travel packages. We developed a prototype system, which obtains users' travel demands from mobile client and generates travel packages containing multiple points of interest and their visiting sequence. Experimental results suggest that the proposed approach shows promise with respect to improving recommendation accuracy and diversity.

源语言英语
文章编号7145457
页(从-至)151-158
页数8
期刊IEEE Transactions on Human-Machine Systems
46
1
DOI
出版状态已出版 - 2月 2016

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