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ASME Press Select Proceedings
Intelligent Engineering Systems through Artificial Neural Networks Volume 18
Editor
ISBN-10:
0791802823
ISBN:
9780791802823
No. of Pages:
700
Publisher:
ASME Press
Publication date:
2008
eBook Chapter
91 Tourism Information Recommender System Using Multiple Recommendation Algorithms Based on Collaborative Filtering
By
Akihiro Yamashita
,
Akihiro Yamashita
Graduate School of Information Science and Technology
Hokkaido University
, Sapporo
, Japan
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Azuma Ohuchi
,
Azuma Ohuchi
Graduate School of Information Science and Technology
Hokkaido University
, Sapporo
, Japan
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Hidenori Kawamura
Hidenori Kawamura
Graduate School of Information Science and Technology
Hokkaido University
, Sapporo
, Japan
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Page Count:
7
-
Published:2008
Citation
Yamashita, A, Ohuchi, A, & Kawamura, H. "Tourism Information Recommender System Using Multiple Recommendation Algorithms Based on Collaborative Filtering." Intelligent Engineering Systems through Artificial Neural Networks Volume 18. Ed. Dagli, CH. ASME Press, 2008.
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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...
Abstract
Introduction
Recommender Systems Based on Collaborative Filtering
Simulation
Results and Discussion
Conclusions
References
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