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Location based learning of user behavior for proactive recommender systems in car comfort functions
2014
Jahrestagung der Gesellschaft für Informatik
In-car comfort functions decrease driving stress and therefore increase safety. Drivers typically do not use all available comfort functions optimally, if at all, in every situation they would offer a substantial increase in comfort. Automating such functions as proactive recommender systems would exploit the full potential for decreasing driver stress. Because comfort functions are highly dependent on the driver's habits, learning the individual user behavior is necessary. We propose a
dblp:conf/gi/StoneBGHJS14
fatcat:xvimdgctzbdsrivp7ly77beihq