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ICDM
2010
IEEE

Mining Public Transport Usage for Personalised Intelligent Transport Systems

8 years 9 months ago
Mining Public Transport Usage for Personalised Intelligent Transport Systems
Traveller information, route planning, and service updates have become essential components of public transport systems: they help people navigate built environments by providing access to information regarding delays and service disruptions. However, one aspect that these systems lack is a way of tailoring the information they offer in order to provide personalised trip time estimates and relevant notifications to each traveller. Mining each user's travel history, collected by automated ticketing systems, has the potential to address this gap. In this work, we analyse one such dataset of travel history on the London underground. We then propose and evaluate methods to (a) predict personalised trip times for the system users and (b) rank stations based on future mobility patterns, in order to identify the subset of stations that are of greatest interest to the user and thus provide useful travel updates.
Neal Lathia, Jon Froehlich, Licia Capra
Added 12 Feb 2011
Updated 12 Feb 2011
Type Journal
Year 2010
Where ICDM
Authors Neal Lathia, Jon Froehlich, Licia Capra
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