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SUMMARY:Mining Public Transport Usage for Personalised Intelligent Transpo
 rt Systems - Neal Lathia (UCL)
DTSTART:20101119T150000Z
DTEND:20101119T153000Z
UID:TALK27817@talks.cam.ac.uk
CONTACT:Eiko Yoneki
DESCRIPTION:Traveller information\, route planning\, and service updates h
 ave become essential components of public transport systems: they help peo
 ple navigate built environments by providing access to information regardi
 ng delays and service disruptions. However\, one aspect that these systems
  invariably 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 automate
 d 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 tim
 es for the system users and (b) rank stations based on future mobility pat
 terns\, in order to identify the subset of stations that are of greatest i
 nterest to each other and thus provide useful travel updates.\n\nNeal's ho
 mepage: http://www.cs.ucl.ac.uk/staff/n.lathia/\n\nThe paper (http://www.c
 s.ucl.ac.uk/staff/n.lathia/papers/lathia_icdm10.pdf) will be presented at 
 IEEE ICDM 2010.
LOCATION:FW26\, Computer Laboratory\, William Gates Builiding
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