Authors:
Jeremias Dötterl
;
Ralf Bruns
and
Jürgen Dunkel
Affiliation:
Hannover University of Applied Sciences and Arts, Germany
Keyword(s):
Situation Awareness, Context Awareness, Decision Support, Recommender Systems, Semantic Web Technologies, Complex Event Processing.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Cloud Computing
;
Enterprise Information Systems
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Semantic Web Technologies
;
Services Science
;
Software Agents and Internet Computing
;
Symbolic Systems
;
User Profiling and Recommender Systems
Abstract:
Nowadays, smartphones and sensor devices can provide a variety of information about a user's current situation. So far, many recommender systems neglect this kind of information and thus cannot provide situation-specific recommendations. Situation-aware recommender systems adapt to changes in the user's environment and therefore are able to offer recommendations that are more appropriate for the current situation. In this paper, we present a software architecture that enables situation awareness for arbitrary recommendation techniques. The proposed system considers both (semi-)static user profiles and volatile situational knowledge to obtain meaningful recommendations. Furthermore, the implementation of the architecture in a museum of natural history is presented, which uses Complex Event Processing to achieve situation awareness.