http://www.cnr.it/ontology/cnr/individuo/prodotto/ID293726
On planning sightseeing tours with TripBuilder (Articolo in rivista)
- Type
- Label
- On planning sightseeing tours with TripBuilder (Articolo in rivista) (literal)
- Anno
- 2014-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1016/j.ipm.2014.10.003 (literal)
- Alternative label
Brilhante I. R., Macedo J. A., Nardini F. M., Perego R., Renso C. (2014)
On planning sightseeing tours with TripBuilder
in Information processing & management; Elsevier, Amsterdam (Paesi Bassi)
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- Brilhante I. R., Macedo J. A., Nardini F. M., Perego R., Renso C. (literal)
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- http://www.sciencedirect.com/science/article/pii/S0306457314000922 (literal)
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- University of Ceara, Brazil; University of Ceara, Brazil; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy (literal)
- Titolo
- On planning sightseeing tours with TripBuilder (literal)
- Abstract
- 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. (literal)
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