Web intelligence for tourism using railway data by a simplified fuzzy reasoning method

Authors:
Takashi Hasuike;Takumi Ichimura
Affiliations:
Graduate School of Information Science and Technology, Osaka University, Suita, Osaka, Japan;Faculty of Management and Information Systems, Prefectural University of Hiroshima, Hiroshima, Japan
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
Year:
2013

Citing 3
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Special issue: Computational intelligence models for image processing and information reasoning

Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning

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Abstract

This paper proposes an approach to analyze the tourism information and data derived from the Web, particularly seat availability data of bullet trains in Japan, and to discover some useful knowledge for the tourism. For the fast development of information and communication technologies, the relation between the web data and tourism is inseparable. However, the Web data include various types of information such as numerical, linguistic, and graded data. Furthermore, the expert tourism planner's subjectivity is also an important factor to develop new favorable plans. A simplified fuzzy reasoning method, which is one of the useful approaches in Data mining, is introduced in order to deal with these data mathematically. The analysis of the tourism data and the knowledge discovery are performed using actual data of bullet trains in Japan.