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Personalized, context-aware intermodal travel information

: Samsel, Christian; Krempels, Karl-Heinz; Garbereder, Gerrit


Majchrzak, T.A. ; Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setubal:
WEBIST 2016, 12th International Conference on Web Information Systems and Technologies. Proceedings. Vol.1 : Rome, Italy, April 23-25, 2016
SciTePress, 2016
ISBN: 978-989-758-186-1
International Conference on Web Information Systems and Technologies (WEBIST) <12, 2016, Rome>
Conference Paper
Fraunhofer FIT ()

The integration of heterogeneous mobility services increases the number of itinerary choices exponentially. To support travelers with the selection of such an intermodal itinerary this work proposes the use of a recommendation system. The developed framework rates intermodal itineraries supplied by an external travel information system based on learned personal preferences and user context (e.g. weather). This rating can be used by the client application (e.g. a mobile app) for sorting or a five-star rating. The framework realizes a set of interfaces to extract feature data of the user context and the possible itineraries and applies a combination of item-based and context-based recommendation algorithms. As evaluation an online questionnaire (n = 101) applying the framework was conducted to assess the feasibility of the approach. The number of participants preferring the personalized and context-aware itinerary presentation compared to the traditional departure time-based presentation was significant. Furthermore it could be verified that a mobility self-assessment is suitable as initial training data.