How to predict journey destination for supporting contextual intelligent information services?

dc.contributor.author Vera Lúcia Costa en
dc.contributor.author Tânia Daniela Fontes en
dc.contributor.author Costa,PM en
dc.contributor.author Teresa Galvão en
dc.date.accessioned 2017-12-20T16:27:55Z
dc.date.available 2017-12-20T16:27:55Z
dc.date.issued 2015 en
dc.description.abstract The adoption of smart cards in urban public transport has fundamentally changed how transport providers manage and plan their networks. Traveller information services, in particular, have leveraged this contextual data for targeting passengers and providing relevant information. Thus, it becomes increasingly relevant for the next generation of services to obtain on-time contextual passenger information, to support the development of intelligent information services. In this paper an adaptation of the Top-K algorithm is proposed for predicting journey destination, applied to different scenarios in public transport. The performance and efficiency are analysed and compared to a decision tree classifier. Finally, the feasibility and potential of applying the proposed methods to large-scale systems in a real-world environment is discussed. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/4526
dc.identifier.uri http://dx.doi.org/10.1109/itsc.2015.474 en
dc.language eng en
dc.relation 6614 en
dc.relation 5986 en
dc.relation 6987 en
dc.rights info:eu-repo/semantics/embargoedAccess en
dc.title How to predict journey destination for supporting contextual intelligent information services? en
dc.type conferenceObject en
dc.type Publication en
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