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- W2742467939 abstract "We introduce a decision-theoretic framework based on Description Logics(DLs), which can be used to encode and solve single stage multi-attribute decision problems. In particular, we consider the background knowledge as a DLknowledge base where each attribute is represented by a concept, weighted bya utility value which is asserted by the user. This yields a compact representation of preferences over attributes. Moreover, we represent choices as knowledgebase individuals, and induce a ranking via the aggregation of attributes thatthey satisfy. We discuss the benefits of the approach from a decision theorypoint of view. Furthermore, we introduce an implementation of the frameworkas a Protege plugin called uDecide. The plugin takes as input an ontology asbackground knowledge, and returns the choices consistent with the user’s (theknowledge base) preferences. We describe a use case with data from DBpedia.We also provide empirical results for its performance in the size of the ontologyusing the reasoner Konclude." @default.
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- W2742467939 date "2017-08-01" @default.
- W2742467939 modified "2023-09-28" @default.
- W2742467939 title "Multi-attribute decision making with weighted description logics" @default.
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