Title
A Personalized Tourist Trip Design Algorithm For Mobile Tourist Guides
Abstract
Mobile tourist guides evolve towards automated personalized tour planning devices. The contribution of this article is to put forward a combined artificial intelligence and metaheuristic approach to solve tourist trip design problems (TTDP). The approach enables fast decision support for tourists on small footprint mobile devices. The orienteering problem, which originates in the operational research literature, is used as a starting point for modelling the TTDP. The problem involves a set of possible locations having a score and the objective is to maximize the total score of the visited locations, while keeping the total time (or distance) below the available time budget. The score of a location represents the interest of a tourist in that location. Scores are calculated using the vector space model, which is a well-known technique from the field of information retrieval. The TTDP is solved using a guided local search metaheuristic. In order to compare the performance of this approach with an algorithm that appeared in the literature, both are applied to a real data set from the city of Ghent. A collection of tourist points of interest with descriptions was indexed and subsequently queried with popular interests, which resulted in a test set of TTDPs. The approach presented in this article turns out to be faster and produces solutions of better quality.
Year
DOI
Venue
2008
10.1080/08839510802379626
Applied Artificial Intelligence
Keywords
Field
DocType
mobile tourist guides,popular interest,local search metaheuristic,mobile tourist guide,orienteering problem,metaheuristic approach,operational research literature,total score,tourist point,available time budget,personalized tourist trip design,tourist trip design problem,mobile device,point of interest,information retrieval,artificial intelligent,operations research,guided local search,vector space model,decision support
Guided Local Search,Computer science,Orienteering,Artificial intelligence,Vector space model,Metaheuristic,Decision support system,Algorithm,Operations research,Mobile device,Point of interest,Machine learning,Test set
Journal
Volume
Issue
ISSN
22
10
0883-9514
Citations 
PageRank 
References 
71
3.02
14
Authors
5
Name
Order
Citations
PageRank
Wouter Souffriau175028.50
Pieter Vansteenwegen2102648.63
Joris Vertommen3985.10
Greet Vanden Berghe4137177.56
Dirk Van Oudheusden591741.64