A decision tree based recommendation system for tourists

Thiengburanathum, Pree, Cang, Shuang and Yu, Hongnian (2015) A decision tree based recommendation system for tourists. In: 2015 21st International Conference on Automation and Computing (ICAC). IEEE. ISBN 978-0-9926-8011-4

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Abstract

Choosing a tourist destination from the information that is available on the Internet and through other sources is one of the most complex tasks for tourists when planning travel, both before and during travel. Previous Travel Recommendation Systems (TRSs) have attempted to solve this problem. However, some of the technical aspects such as system accuracy and the practical aspects such as usability and satisfaction have been neglected. To address this issue, it requires a full understanding of the tourists' decision-making and novel models for their information search process. This paper proposes a novel human-centric TRS that recommends destinations to tourists in an unfamiliar city. It considers both technical and practical aspects using a real world data set we collected. The system is developed using a two-steps feature selection method to reduce number of inputs to the system and recommendations are provided by decision tree C4.5. The experimental results show that the proposed TRS can provide personalized recommendation on tourist destinations that satisfy the tourists.

Item Type:	Book Section
Uncontrolled Keywords:	Recommendation System, Tourist Destination, Feature Selection, Filtering methods, Mutual information, Classification, Decision Tree
Subjects:	G400 Computer Science
Department:	Faculties > Business and Law > Newcastle Business School
Depositing User:	Becky Skoyles
Date Deposited:	04 Dec 2018 16:24
Last Modified:	19 Nov 2019 09:49
URI:	http://nrl.northumbria.ac.uk/id/eprint/37078

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