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Context-Aware Tourism Recommender System Using Temporal Ontology and Naïve Bayes

  • Chakkrit Snae NamahootEmail author
  • Michael Brückner
  • Naruepon Panawong
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 361)

Abstract

In this paper, we present a Context Aware Thai Tourism Recommender System (CAT-TOURS) that applies a complex Naïve Bayes Model with boundary values, tourism ontology for Thailand and a temporal ontology to support decision making in tourism. Promising results are presented in the form of precision, recall and F measure for Websites related to Thailand’s tourism industry. We compare the results with those gained with Latent Semantic Indexing (LSI).

This research was guided by the following aims: (1) find a simple method to classify Thai tourism Web documents that contain information on more than one topic, and (2) take into account time constraints in the process of making recommendations.

Keywords

Recommender System Temporal ontology Tourism Naïve Bayes LSI 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Chakkrit Snae Namahoot
    • 1
    Email author
  • Michael Brückner
    • 2
  • Naruepon Panawong
    • 3
  1. 1.Department of Computer Science and Information Technology, Faculty of ScienceNaresuan UniversityPhitsanulokThailand
  2. 2.Department of Educational Technology and Communication, Faculty of EducationNaresuan UniversityPhitsanulokThailand
  3. 3.Department of Applied Science, Faculty of Science and TechnologyNakhon Sawan Rajabhat UniversityNakhon SawanThailand

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