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• W1948930740 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." @default.
• W1948930740 created "2016-06-24" @default.
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• W1948930740 date "2015-09-01" @default.
• W1948930740 modified "2023-09-22" @default.
• W1948930740 title "How to Predict Journey Destination for Supporting Contextual Intelligent Information Services?" @default.
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• W1948930740 doi "https://doi.org/10.1109/itsc.2015.474" @default.
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