A tourism destination recommender system using users' sentiment and temporal dynamics

作者：Zheng, Xiaoyao; Luo, Yonglong^*; Sun, Liping; Zhang, Ji; Chen, Fulong

来源：Journal of Intelligent Information Systems, 2018, 51(3): 557-578.

DOI：10.1007/s10844-018-0496-5

• Recommender system
• Opinion mining
• Sentiment analysis
• Temporal dynamics
• Tourism destination
• Matrix factorization

With the development and popularity of social networks, an increasing number of consumers prefer to order tourism products online, and like to share their experiences on social networks. Searching for tourism destinations online is a difficult task on account of its more restrictive factors. Recommender system can help these users to dispose information overload. However, such a system is affected by the issue of low recommendation accuracy and the cold-start problem. In this paper, we propose a tourism destination recommender system that employs opinion-mining technology to refine user sentiment, and make use of temporal dynamics to represent user preference and destination popularity drifting over time. These elements are then fused with the SVD+ + method by combining user sentiment and temporal influence. Compared with several well-known recommendation approaches, our method achieves improved recommendation accuracy and quality. A series of experimental evaluations, using a publicly available dataset, demonstrates that the proposed recommender system outperforms the existing recommender systems.

• 出版日期2018-12
• 单位安徽师范大学