Design and implementation of an intelligent recommendation system for tourist attractions: The integration of EBM model, Bayesian network and Google Maps

Authors:
Fang-Ming Hsu;Yu-Tzeng Lin;Tu-Kuang Ho
Affiliations:
Department of Information Management, National Dong Hwa University, 1, Sec. 2, Dahsueh Rd., Shoufeng, Hualien 974, Taiwan, ROC;Department of Information Management, National Dong Hwa University, 1, Sec. 2, Dahsueh Rd., Shoufeng, Hualien 974, Taiwan, ROC and Department of Hospitality Management, Taiwan Hospitality & Touris ...;Department of Tourism, Taiwan Hospitality & Tourism College, 268, Chung-Hsing St., Shoufeng, Hualien 974, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

Selecting tourist attractions and collecting related site information is one of the most crucial activities for a tourist when making decisions for a trip. Although various recommendation systems have been discussed over the last decade, rarely do such systems take individual tourist preference information into consideration. Based on the Engel-Blackwell-Miniard (EBM) model, this study used data published by the Tourism Bureau of Taiwan to develop a decision support system for tourist attractions. The probability of a tourist attraction appealing to a particular tourist is calculated utilizing a Bayesian network, and the accuracy of the prediction is validated by a ROC curve test. Finally, recommended routes and tourist attractions are presented through an interactive user interface using Google Maps. This study confirms that by combining the EBM model with a Bayesian network to propose a decision support system called the Intelligent Tourist Attractions System (ITAS). It has demonstrated good prediction of tourism attractions and provides useful map information to tourists.