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Distinguishing Answers in Conceptual Graph Knowledge Bases

Nicolas Moreau 1 Michel Leclère 2 Madalina Croitoru 2
2 GRAPHIK - Graphs for Inferences on Knowledge
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : In knowledge bases, the open world assumption and the ability to express variables may lead to an answer redundancy problem. This problem occurs when the returned answers are comparable. In this paper we define a framework to distinguish amongst answers. Our method will be based on adding contextual knowledge extracted from the KB. The construction of such descriptions allows the clarification of the notion of redundancy between answers, not only based on the images of the requested pattern but on the whole KB. We propose a definition for the set of answers to be computed from a query, which ensures both properties of non-redundancy and completeness. While all answers of this set can be distinguished from others with a description, an open question remains of what is a good description to return to an end-user. We introduce the notion of smart answer and give an algorithm that computes a set of smart answers, based on a vertex neighborhood distance.
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Submitted on : Thursday, April 9, 2009 - 3:52:36 PM
Last modification on : Friday, October 22, 2021 - 3:07:21 PM
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Nicolas Moreau, Michel Leclère, Madalina Croitoru. Distinguishing Answers in Conceptual Graph Knowledge Bases. ICCS: International Conference on Conceptual Structures, Jul 2009, Moscow, Russia. pp.233-246, ⟨10.1007/978-3-642-03079-6_18⟩. ⟨lirmm-00374749⟩



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