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analysisitself.Forthelatter,anumberofotherworkscon-structandrecommendt analysisitself.Forthelatter,anumberofotherworkscon-structandrecommendt

analysisitself.Forthelatter,anumberofotherworkscon-structandrecommendt - PDF document

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analysisitself.Forthelatter,anumberofotherworkscon-structandrecommendt - PPT Presentation

1httpswwwmturkcom Figure1SampleonedayitineraryconstructedbyoursystemforthecityNYClargescaleusercontributedrichmediarepositoriesWeplantoexploremanydirectionssuchasapplyingdi erent lteringan ID: 110726

1https://www.mturk.com/ Figure1:Sampleone-dayitineraryconstructedbyoursystemforthecityNYC.large-scaleusercontributedrichmediarepositories.Weplantoexploremanydirectionssuchasapplyingdi erent lter-ingan

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analysisitself.Forthelatter,anumberofotherworkscon-structandrecommendtouristitinerariesatvariousgranular-ities[3,4].Theyrely,however,onstructuredandcleanseddataonlandmarks,anddonotdealwiththechallengeofanalyzingandextractingfromnoisydata.Ourworkisalsotangentiallyrelatedtoothervast eldssuchasvisualizinggeo-spatialdata,trackingmovementsbasedonsensornet-works,andconstraintoptimization.3.OURAPPROACHThe rststepofourapproachistoconverttherawuserphotosintoindividualtimedpathsforagivencity.Intu-itively,thesepaths,whichconnectvariousPOIs,arecon-structedfromindividualphotostreamsanddescribethemovementsofindividualtourists.Theprocesshasthreemainchallenges:(i)pruningirrelevantphotosthatarenotassociatedwiththecityofinterestornotownedbyatourist;(ii)mappingphotostothePOIsofthecity,and(iii)con-structingindividualtimedpaths.Eachtimedpathisase-quenceofPOIstraversedbyauser,annotatedwiththetimespentbytheuserateachPOIandthetransittimesbetweenpairsofsuccessivePOIs.Weemphasizeherethat:1)whileourstudyfocusonlever-aginginformationfromaparticularrichmediasharingsite,Flickr,theworkiseasilyextensibletoanyothersocialrepos-itory,whereusescansharesemanticallyandgeo-temporallytaggedrichmedia;2)whileweprocesstheinternalYahoo!Flickrdatarepository,thesameprotocolcanessentiallybefollowedbyusingtheopenFlickrAPI.Giventhesetoftimedpaths,ourgoalistoaggregatetheactionsofmanyindividualtravelersintocoherentitinerarieswhiletakingintoconsiderationPOIpopularity.Tothise ect,wede nerepresentedtimedpathsasagraphandformulatetheproblemof ndinganitinerarybetweentwopointsgivenatimeconstraint.WereducethisproblemtothedirectedOrienteeringproblemandusearestatementofChekuriandPal'salgorithm[1].4.OURFINDINGSWeevaluatethequalityoftravelitinerariesconstructedbyoursysteminanextensiveuserstudyconductedthroughtheAmazonMechanicalTurk(AMT)1system.Anexampleone-dayitinerarygeneratedbyourmethodisshowninFig-ure1.Ourexperimentalstudyelicitedfeedbackfrom250workersonAMTinordertovalidateoursystem'sabilitytogeneratehighqualitytravelitinerariesforpopulartouristiccities,includingBarcelona,London,NewYorkCity(NYC),Paris,andSanFrancisco.Thequestionnaireevaluateddi-verseaspectsofoursystemgenerateditinerariessuchasitsoverallusefulnessaswellasitsrelevanceintermsofthetransitandvisittimestoeachPOI.Weshowthatusersperceiveourautomaticallygenerateditinerariesasbeingasgoodas(orevenslightlybetterthan)itinerariesprovidedbyprofessionaltourcompanies.Fur-thermore,weshowthatusersaresatis edwiththerec-ommendedtransitandvisittimesforthePOIswithintheitineraries.5.CONCLUSIONThispaperaddressedthequestionofautomaticgener-ationoftravelitinerariesforpopulartouristiccitiesfrom 1https://www.mturk.com/ Figure1:Sampleone-dayitineraryconstructedbyoursystemforthecityNYC.large-scaleusercontributedrichmediarepositories.Weplantoexploremanydirectionssuchasapplyingdi erent lter-ingandaggregationtechniquestoaccommodatedi erenttypesoftravelers,andconstructing\o thebeatentrack"itinerariesthatcatertonicheaudiencesratherthanmain-streamcrowds.6.REFERENCES[1]ChandraChekuriandMartinPal.Arecursivegreedyalgorithmforwalksindirectedgraphs.InFOCS,pages245{253,2005.[2]DavidCrandall,LarsBackstrom,DanielHuttenlocher,andJonKleinberg.Mappingtheworld'sphotos.InProc.18thInternationalWorldWideWebConference(WWW'2009),pages761{770,April2009.[3]DavidLeakeandJayPowell.Mininglarge-scaleknowledgesourcesforcaseadaptationknowledge.InProc.ICCBR2007,pages209{223,2007.[4]DavidLeakeandJayPowell.Knowledgeplanningandlearnedpersonalizationforweb-basedcaseadaptation.InProc.ECCBR2008,pages284{298,2008.[5]AdrianPopescuandGregoryGrefenstette.Deducingtriprelatedinformationfrom ickr.InProc.18thInternationalWorldWideWebConference(WWW'2009),pages1183{1184,April2009.[6]TyeRattenbury,NathanielGood,andMorNaaman.Towardautomaticextractionofeventandplacesemanticsfrom ickrtags.InProc.30thAnnualInternationalACMSIGIRConferenceonResearchandDevelopmentinInformationRetrieval(SIGIR'07),pages103{110,July2007.[7]ChihHuaTai,DeNianYang,LungTsaiLin,andMingSyanChen.Recommendingpersonalizedscenicitinerarywithgeo-taggedphotos.InProc.IEEEInternationalConferenceonMultimediaandExpo(ICME'2008),pages1209{1212,2008.

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