Abstract
In the era of information explosion, the Internet has become one of the most important tools for users to get information. As one of the main applications, most of the tourists, if not all, utilize the search engine to obtain the useful travelling information online which makes tourism recommender systems valuable. However, given a huge amount of online information, it still remains challenging to develop an effective tourism recommender system. To tackle this challenge, in this work, we propose TRSO, an ontology-based tourism recommender system by incorporating different techniques. First, we adopt the association rules to dig out the associated users from a large number of users. By doing so, users in the database are divided into two categories: related users and unrelated users. Second, for the related users, we propose a collaborative filtering algorithm by incorporating the time and evaluation factors. For the unrelated users, we utilize a different collaborative filtering algorithm, which integrates the time factor and the tourism attraction ontology information. Third, we further filter useless information according to the context information. Finally, we expand the tourism attraction with other tourism information such as shopping, eating and traveling based on a tourism ontology. The experimental results on the standard benchmark show that the proposed tourism recommendation algorithm can achieve satisfactory and comprehensive recommendation performance.
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Acknowledgments
The work is supported by the National Natural Science Foundation of China under Grant No. 61272185, the Natural Science Foundation of Heilongjiang Province of China under Grant No. F201340, the Science Foundation of Heilongjiang Province of China for returned scholars under Grant No. LC2015025, the Fundamental Research Funds for Central University under Grant No. HEUCF160602, and Harbin Special Fund for innovative talents of science and technology research under Grant No. 2013RFQXJ113.
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Chu, Y., Wang, H., Zheng, L., Wang, Z., Tan, KL. (2016). TRSO: A Tourism Recommender System Based on Ontology. In: Lehner, F., Fteimi, N. (eds) Knowledge Science, Engineering and Management. KSEM 2016. Lecture Notes in Computer Science(), vol 9983. Springer, Cham. https://doi.org/10.1007/978-3-319-47650-6_45
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DOI: https://doi.org/10.1007/978-3-319-47650-6_45
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