Advanced Recommendation Models for Mobile Tourist Information

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dc.contributor.authorHinze, Annika
dc.contributor.authorJunmanee, Saijai
dc.coverage.spatialConference held at Montpellier, Franceen_NZ
dc.date.accessioned2009-01-09T00:18:44Z
dc.date.available2009-01-09T00:18:44Z
dc.date.issued2006
dc.description.abstractPersonalized recommendations in a mobile tourist information system suffer from a number of limitations. Most pronounced is the amount of initial user information needed to build a user model. In this paper, we adopt and extend the basic concepts of recommendation paradigms by exploiting a user’s personal information (e.g., preferences, travel histories) to replace the missing information. The designed algorithms are embedded as recommendation services in our TIP prototype. We report on the results of our analysis regarding effectiveness and performance of the recommendation algorithms. We show how a number of limiting factors were successfully eliminated by our new recommender strategies.en
dc.identifier.citationHinze, A. & Junmanee, S. (2006). Advanced Recommendation Models for Mobile Tourist Information. In R. Meersman & Z. Tari et al. (Eds), Proceedings of OTM Confederated International Conferences, CoopIS, DOA, GADA, and ODBASE 2006, Montpellier, France, October 29 - November 3, 2006. (pp. 643-660). Berlin, Germany: Springer.en
dc.identifier.doi10.1007/11914853_38en
dc.identifier.urihttps://hdl.handle.net/10289/1755
dc.language.isoen
dc.publisherSpringer Berlinen
dc.relation.isPartOfOn the Move to Meaningful Internet Systems 2006: CoopIS, DOA, GADA, and ODBASE, Part Ien_NZ
dc.relation.urihttp://www.springerlink.com/content/x317160204w32t26/en
dc.sourceOTM 2006en_NZ
dc.subjectcomputer scienceen
dc.subjectmobile tourist informationen
dc.titleAdvanced Recommendation Models for Mobile Tourist Informationen
dc.typeConference Contributionen
pubs.begin-page643en_NZ
pubs.elements-id17166
pubs.end-page660en_NZ
pubs.finish-date2006-11-03en_NZ
pubs.place-of-publicationBerlinen_NZ
pubs.start-date2006-10-29en_NZ
pubs.volumeLNCS 4275en_NZ
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