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A personalized tourist trip design algorithm for mobile tourist guides

Wouter Souffriau, Pieter Vansteenwegen UGent, Joris Vertommen, Greet Vanden Berghe and Dirk Van Oudheusden (2008) APPLIED ARTIFICIAL INTELLIGENCE. 22(10). p.964-985
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.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
ORIENTEERING PROBLEM
journal title
APPLIED ARTIFICIAL INTELLIGENCE
Appl. Artif. Intell.
volume
22
issue
10
pages
964 - 985
Web of Science type
Article
Web of Science id
000262292300002
JCR category
ENGINEERING, ELECTRICAL & ELECTRONIC
JCR impact factor
0.795 (2008)
JCR rank
138/229 (2008)
JCR quartile
3 (2008)
ISSN
0883-9514
DOI
10.1080/08839510802379626
language
English
UGent publication?
no
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1143687
handle
http://hdl.handle.net/1854/LU-1143687
date created
2011-02-09 13:50:27
date last changed
2016-12-19 15:46:05
@article{1143687,
  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.},
  author       = {Souffriau, Wouter and Vansteenwegen, Pieter and Vertommen, Joris and Vanden Berghe, Greet and Van Oudheusden, Dirk},
  issn         = {0883-9514},
  journal      = {APPLIED ARTIFICIAL INTELLIGENCE},
  keyword      = {ORIENTEERING PROBLEM},
  language     = {eng},
  number       = {10},
  pages        = {964--985},
  title        = {A personalized tourist trip design algorithm for mobile tourist guides},
  url          = {http://dx.doi.org/10.1080/08839510802379626},
  volume       = {22},
  year         = {2008},
}

Chicago
Souffriau, Wouter, Pieter Vansteenwegen, Joris Vertommen, Greet Vanden Berghe, and Dirk Van Oudheusden. 2008. “A Personalized Tourist Trip Design Algorithm for Mobile Tourist Guides.” Applied Artificial Intelligence 22 (10): 964–985.
APA
Souffriau, W., Vansteenwegen, P., Vertommen, J., Vanden Berghe, G., & Van Oudheusden, D. (2008). A personalized tourist trip design algorithm for mobile tourist guides. APPLIED ARTIFICIAL INTELLIGENCE, 22(10), 964–985.
Vancouver
1.
Souffriau W, Vansteenwegen P, Vertommen J, Vanden Berghe G, Van Oudheusden D. A personalized tourist trip design algorithm for mobile tourist guides. APPLIED ARTIFICIAL INTELLIGENCE. 2008;22(10):964–85.
MLA
Souffriau, Wouter, Pieter Vansteenwegen, Joris Vertommen, et al. “A Personalized Tourist Trip Design Algorithm for Mobile Tourist Guides.” APPLIED ARTIFICIAL INTELLIGENCE 22.10 (2008): 964–985. Print.