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Food tour recommendation using modified ant colony algorithm

Sriphaew, Kritsada and Sombatsricharoen, Kannita (2015) Food tour recommendation using modified ant colony algorithm. In: 5th International Conference on Computing and Informatics (ICOCI) 2015, 11-13 August 2015, Istanbul, Turkey.

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Food tour is popular and becomes one of the most dynamic and creative segments of tourism.Popular itinerary of food tour can be extracted from the information in the Internet, but preference of the user must also be taken into consideration.This paper proposed a modified Ant Colony algorithm to find best possible itineraries through approximation and heuristic method by taking majority preferences of users into account when computing the recommended itinerary.The experiments were conducted on a food tour of restaurants in Yaowarat, a Bangkok’s China-town of Thailand.The results show that our proposed algorithm can recommend itineraries with rank-accuracy 0.88-0.97, which is better than the original Ant Colony algorithm with rank-accuracy 0.61-0.63.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN No: 978-967-0910-02-4 Jointly organized by: Universiti Utara Malaysia & Istanbul Zaim University
Uncontrolled Keywords: food tour, recommendation system, ant colony, tourism
Subjects: G Geography. Anthropology. Recreation > G Geography (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Computing
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 01 Oct 2015 06:03
Last Modified: 28 Apr 2016 01:11

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