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

Takashi Hasuike, Takumi Ichimura

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)251-259
Number of pages9
JournalJournal of Intelligent and Fuzzy Systems
Volume24
Issue number2
DOIs
Publication statusPublished - 2013 Feb 15

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Keywords

  • Tourism information
  • Web intelligence
  • data mining
  • fuzzy reasoning method

ASJC Scopus subject areas

  • Statistics and Probability
  • Engineering(all)
  • Artificial Intelligence

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