TSACO: extending a context-aware recommendation system with allen temporal operators

UCAmI'12 Proceedings of the 6th international conference on Ubiquitous Computing and Ambient Intelligence(2012)

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Abstract
In this paper we present our research to extend a recommender system based on a semantic multicriteria ant colony algorithm to allow the use of Allen temporal operators. The system utilizes user's learnt routes, including their associated context information, in order to predict the most likely route a user is following, given his current location and context data. The addition of temporal operators will increase the level of expressiveness of the queries the system can answer what will allow, in turn, more fine-tuned predictions. This more refined knowledge could then be used as the basis for offering services related to his current (or most likely future) context in the vicinity of the path the user is following.
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Key words
fine-tuned prediction,recommender system,temporal operator,context data,likely future,likely route,allen temporal operator,associated context information,context-aware recommendation system,current location,system utilizes user,semantic search
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