A tourism destination recommender system using users' sentiment and temporal dynamics
Article
Article Title | A tourism destination recommender system using users' sentiment and temporal dynamics |
---|---|
ERA Journal ID | 18019 |
Article Category | Article |
Authors | Zheng, Xiaoyao (Author), Luo, Yonglong (Author), Sun, Liping (Author), Zhang, Ji (Author) and Chen, Fulong (Author) |
Journal Title | Journal of Intelligent Information Systems |
Journal Citation | 51 (3), pp. 557-578 |
Number of Pages | 22 |
Year | 2018 |
Place of Publication | Dordrecht, Netherlands |
ISSN | 0925-9902 |
1573-7675 | |
Digital Object Identifier (DOI) | https://doi.org/10.1007/s10844-018-0496-5 |
Web Address (URL) | https://link.springer.com/article/10.1007%2Fs10844-018-0496-5 |
Abstract | 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. |
Keywords | recommender systems; rating; recommendation algorithm |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Anhui Normal University, China |
Faculty of Health, Engineering and Sciences | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q52vv/a-tourism-destination-recommender-system-using-users-sentiment-and-temporal-dynamics
243
total views9
total downloads2
views this month0
downloads this month