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Intelligent tourism recommender systems A survey

Review

Intelligenttourismrecommendersystems:A

survey

JoanBorràsa,b, ,AntonioMorenob,AidaVallsb

Science&TechnologyParkforTourismandLeisure,C/JoanotMartorell,15,43480Vila-Seca,Catalonia,Spain

IntelligentTechnologiesforAdvancedKnowledgeAcquisition(ITAKA),Departamentd’EnginyeriaInformàticaiMatemàtiques,UniversitatRoviraiVirgili,Av.PaïsosCatalans,26,43007Tarragona,Catalonia,Spain

ba

articleinfoabstract

Recommendersystemsarecurrentlybeingappliedinmanydifferentdomains.Thispaperfocusesontheirapplicationintourism.Acomprehensiveandthoroughsearchofthesmarte-Tourismrecommend-ersreportedintheArti cialIntelligencejournalsandconferencessince2008hasbeenmade.Thepaperprovidesadetailedandup-to-datesurveyofthe eld,consideringthedifferentkindsofinterfaces,thediversityofrecommendationalgorithms,thefunctionalitiesofferedbythesesystemsandtheiruseofArti cialIntelligencetechniques.Thesurveyalsoprovidessomeguidelinesfortheconstructionoftour-ismrecommendersandoutlinesthemostpromisingareasofworkinthe eldforthenextyears.

Ó2014ElsevierLtd.Allrightsreserved.

Articlehistory:

Availableonline9June2014Keywords:

RecommendersystemsTourismOntologiesPlanningClustering

1.Introduction

,suchasaccommodations,restaurants,museumsorevents,amongoth-ers,iscommonlysearchedfortouristsinordertoplanatrip.How-ever,thelistofpossibilitiesofferedbyWebsearchengines(orevenspecialisedtourismsites)maybeoverwhelming.Theevaluationofthislonglistofoptionsisverycomplexandtimeconsumingfortouristsinordertoselecttheonethat tsbetterwiththeirneeds.Personalizationtechniques(Gao,Liu,&Wu,2010)aimtoprovidecustomisedinformationtousersbasedontheirpreferences,restrictionsortastes.Theyareparticularlyrelevantinrecom-mendersystems(Adomavicius&Tuzhilin,2005),whoseobjectiveisto lterirrelevantoptionsandtoprovidepersonalisedandrele-vantinformationtoeachparticularuser.Inthetourism eld,travelrecommendersystems(Ricci,2002)aimtomatchthecharacteris-ticsoftourismandleisureresourcesorattractionswiththeuserneeds.Thesesystemsareespeciallyusefuliftheycanautomati-callylearntheuser’spreferencesthroughtheanalysisofherexpli-citorimplicitfeedback(Sieg,Mobasher,&Burke,2007).Explicit

datamaybegivenbytheuserindifferentways,forinstancewhenevershespeci esherculturalinterestsby llinginaform.Implicitinterestscanbeinferredbythesystemthroughtheanalysisofthebehaviouroftheuser.

Inmanycasesrecommendersystemsnotonlytakeintoaccountthepreferencesofthetouristbuttheyalsoanalyzethedynamiccontext(Dey&Abowd,1999)ofthetrip.Thisisespeciallyusefulwhentouristsarealreadyatthedestinationandtheyarewillingtousetheirmobiledevicestocustomisetheirtripsinrealtime.Thecontextcanincludeaspectslikethetourist’slocation,thetimeofthevisitorthecurrentweather(Lamsfus,Alzua-Sorzabal,Martin,Salvador,&Usandizaga,2009).Approachesthattakecon-textintoaccountcansendsuggestionsproactively,dependingonthecurrentstateofthetourist.Forexample,amuseumthatwasplannedtobevisitedtodaymaybetoofarfromthevisitorandshemaynothaveenoughtimetoreachit,sotheplanscheduledfortomorrowmaybechangedtoincludethevisittothemuseum.Thelasttenyearshavewitnessedanexplosiveincreaseintheuseofmobiletechnologyamongtourists.Therefore,e-Tourismsystems(Buhalis,2003)provideagoodopportunityformobileser-vicesthathelpvisitorsbyofferingrecommendationsbasedontheirpreferencesandtheircurrentcontext.

ThispaperfocusesontourismrecommendersystemsthatemployArti cialIntelligence(AI)techniquesatsomepoint.Someexamplescanbethefollowing:

Intelligentautonomousagentsmayanalysethebehaviourofauser,learnautomaticallytheuserpro leandprovideproactiverecommendationsdependingonthecurrentcontext(Batet,Moreno,Sánchez,Isern,&Valls,2012).

Correspondingauthorat:Science&TechnologyParkforTourismandLeisure,C/

JoanotMartorell,15,43480Vila-Seca,Catalonia,Spain.Tel.:+34977394754.

E-mailaddresses:joan.borras@pct-turisme.cat(J.Borràs),antonio.moreno@urv.cat(A.Moreno),aida.valls@urv.cat(A.Valls).

0957-4174/Ó2014ElsevierLtd.Allrightsreserved.

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