Estimation of travel contexts from longitudinal behavioural data

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Recent advances of information technologies enable us to obtain huge and continuous log data on travel behaviour. For example, a survey using GPS equipped mobile phone is often performed. Also the smart card systems used by the payment of transport systems collect huge data on travellers' usage of the transport systems. However, the methodologies of estimating travel contexts from such longitudinal log data are not still established. This study developed the methods to estimate travel contexts from the longitudinal behavioural log data, based on the methods of the natural language processing.