http://www.cnr.it/ontology/cnr/individuo/prodotto/ID221002
A trajectory-based recommender system for tourism. (Contributo in atti di convegno)
- Type
- Label
- A trajectory-based recommender system for tourism. (Contributo in atti di convegno) (literal)
- Anno
- 2012-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1007/978-3-642-35236-2_20 (literal)
- Alternative label
Baraglia R., Frattari C., Muntean C. I., Nardini F. M., Silvestri F. (2012)
A trajectory-based recommender system for tourism.
in Active Media Technology. 8th International Conference, Macau, China, 4-7 December 2012
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Baraglia R., Frattari C., Muntean C. I., Nardini F. M., Silvestri F. (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
- ID PUMA:cnr.isti/2012-A2-058
Progetto VIsual Support to Interactive TOurism in Tuscany: Acronimo VISITO Tuscany: Grant agreement D57E09000050007: Tipo Progetto EU_FP7 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://link.springer.com/chapter/10.1007/978-3-642-35236-2_20 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- CNR-ISTI, Pisa; University of Pisa, Italy; Babes-Bolyai University, Cluj-Napoca, Romania (literal)
- Titolo
- A trajectory-based recommender system for tourism. (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- 978-3-642-35235-5 (literal)
- Abstract
- Recommendation systems provide focused information to users on a set of objects belonging to a specific domain. The proposed recommender system provides personalized suggestions about touristic points of interest. The system generates recommendations, consisting of touristic places, according to the current position of a tourist and previously collected data describing tourist movements in a touristic location/city. The touristic sites correspond to a set of points of interest identified a priori. We propose several metrics to evaluate both the spatial coverage of the dataset and the quality of recommendations produced. We assess our system on two datasets: a real and a synthetic one. Results show that our solution is a viable one. (literal)
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