PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Brilhante I. R., Macedo J. A., Nardini F. M., Perego R., Renso C. On planning sightseeing tours with TripBuilder. In: Information Processing & Management, vol. 51 (2) pp. 1 - 15. Elsevier, 2015. [Online First 30 October 2014]
 
 
Abstract
(English)
We propose TripBuilder, an unsupervised framework for planning personalized sightseeing tours in cities. We collect categorized Points of Interests (PoIs) from Wikipedia and albums of geo-referenced photos from Flickr. By considering the photos as traces revealing the behaviors of tourists during their sightseeing tours, we extract from photo albums spatio-temporal information about the itineraries made by tourists, and we match these itineraries to the Points of Interest (PoIs) of the city. The task of recommending a personalized sightseeing tour is modeled as an instance of the Generalized Maximum Coverage (GMC) problem, where a measure of personal interest for the user given her preferences and visiting time-budget is maximized. The set of actual trajectories resulting from the GMC solution is scheduled on the tourist's agenda by exploiting a particular instance of the Traveling Salesman Problem (TSP). Experimental results on three different cities show that our approach is effective, efficient and outperforms competitive baselines.
URL: http://www.sciencedirect.com/science/article/pii/S0306457314000922
DOI: 10.1016/j.ipm.2014.10.003
Subject Recommender systems
Trajectory mining
Sightseeing tours
H.3.3 Information Search and Retrieval


Icona documento 1) Download Document PDF


Icona documento Open access Icona documento Restricted Icona documento Private

 


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional