Intelligent Engineering Systems through Artificial Neural Networks Volume 18
91 Tourism Information Recommender System Using Multiple Recommendation Algorithms Based on Collaborative Filtering
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- Ris (Zotero)
- Reference Manager
Large amounts of tourism information on websites help individual tourists to plan their trips. At the same time, because the expansion of information overload problem, users have to invest a lot of time and effort to find satisfactory information or products. In this situation, a recommender system, which provides personalized predictions, is attracting attention in many E-commerce sites as one of the solution to reduce the problem. In this paper, we investigate the accuracy of traditional recommendation algorithms under several conditions using multi-agent simulation. Moreover, we propose a tourism information system with personalized recommendation using a new method of appropriately switching multiple recommendation algorithms.