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

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2015

Autores

Costa, V. (Autor) FEUP; Costa, PM (Autor) Outra; Teresa Galvão Dias (Autor) FEUP

Ata de Conferência Internacional

Título: 2015 IEEE 18th International Conference on Intelligent Transportation Systems

Páginas: 2959-2964

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 2 Citações

Outras Informações

ID Authenticus: P-00K-164

DOI: 10.1109/itsc.2015.474

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6