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15
Managing uncertainty and vagueness in description logics, logic programs and description logic programs
, 2008
"... Managing uncertainty and/or vagueness is starting to play an important role in Semantic Web representation languages. Our aim is to overview basic concepts on representing uncertain and vague knowledge in current Semantic Web ontology and rule languages (and their combination). ..."
Abstract

Cited by 16 (5 self)
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Managing uncertainty and/or vagueness is starting to play an important role in Semantic Web representation languages. Our aim is to overview basic concepts on representing uncertain and vague knowledge in current Semantic Web ontology and rule languages (and their combination).
Annotated answer set programming
 In: Proceedings of the 11th International Conference on Information Processing and Management of Uncertainty in KnowledgeBased Systems (IPMU06
, 2006
"... We present Annotated Answer Set Programming, that extends the expressive power of disjunctive logic programming with annotation terms, taken from the generalized annotated logic programming framework. ..."
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Cited by 7 (0 self)
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We present Annotated Answer Set Programming, that extends the expressive power of disjunctive logic programming with annotation terms, taken from the generalized annotated logic programming framework.
A connection between Similarity Logic Programming and Gödel Modal Logic
"... In this paper we relate two logical similaritybased approaches to approximate reasoning. One approach extends the framework of (propositional) classical logic programming by introducing a similarity relation in the alphabet of the language that allows for an extended unification procedure. The seco ..."
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Cited by 2 (2 self)
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In this paper we relate two logical similaritybased approaches to approximate reasoning. One approach extends the framework of (propositional) classical logic programming by introducing a similarity relation in the alphabet of the language that allows for an extended unification procedure. The second approach is a manyvalued modal logic approach where ✸p is understood as approximately p. Here, the similarity relations are introduced at the level of the Kripke models where possible worlds can be similar to some extent. We show that the former approach can be expressed inside the latter.
A SimilarityBased Unification Model for Flexible Querying
, 2002
"... We use the formal model for similaritybased fuzzy unification in multiadjoint logic programs to provide new tools for flexible querying. Our approach is based on a general framework for logic programming, which gives a formal model of fuzzy logic programming extended by fuzzy similarities and ..."
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Cited by 1 (1 self)
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We use the formal model for similaritybased fuzzy unification in multiadjoint logic programs to provide new tools for flexible querying. Our approach is based on a general framework for logic programming, which gives a formal model of fuzzy logic programming extended by fuzzy similarities and axioms of firstorder logic with equality.
A connection between Similarity Logic Programming and Gödel Modal Logic
"... Abstract. In this paper we relate two logical similaritybased approaches to approximate reasoning. One approach extends the framework of (propositional) classical logic programming by introducing a similarity relation in the alphabet of the language that allows for an extended unification procedure ..."
Abstract
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Abstract. In this paper we relate two logical similaritybased approaches to approximate reasoning. One approach extends the framework of (propositional) classical logic programming by introducing a similarity relation in the alphabet of the language that allows for an extended unification procedure. The second approach is a manyvalued modal logic approach where ✸p is understood as approximately p. Here, the similarity relations are introduced at the level of the Kripke models where possible worlds can be similar to some extent. We show that the former approach can be expressed inside the latter.
EUSFLAT LFA 2005 A connection between Similarity Logic Programming and Gödel Modal Logic
"... In this paper we relate two logical similaritybased approaches to approximate reasoning. One approach extends the framework of (propositional) classical logic programming by introducing a similarity relation in the alphabet of the language that allows for an extended unification procedure. The seco ..."
Abstract
 Add to MetaCart
In this paper we relate two logical similaritybased approaches to approximate reasoning. One approach extends the framework of (propositional) classical logic programming by introducing a similarity relation in the alphabet of the language that allows for an extended unification procedure. The second approach is a manyvalued modal logic approach where ✸p is understood as approximately p. Here, the similarity relations are introduced at the level of the Kripke models where possible worlds can be similar to some extent. We show that the former approach can be expressed inside the latter.
EUSFLAT LFA 2005 Fuzzy logic as an optimization task
"... We present a model of fuzzy logic programming with best answer semantics as an optimization task and discuss various utility function problems. ..."
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We present a model of fuzzy logic programming with best answer semantics as an optimization task and discuss various utility function problems.
Incomplete Fuzzy Information in Prolog
"... Incomplete information is a problem in many aspects of actual environments. In many sceneries the knowledge is not represented in a crisp way. It is common to find fuzzy concepts or problems with some level of uncertainty. It is difficult to find practical systems which handle fuzziness and uncertai ..."
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Incomplete information is a problem in many aspects of actual environments. In many sceneries the knowledge is not represented in a crisp way. It is common to find fuzzy concepts or problems with some level of uncertainty. It is difficult to find practical systems which handle fuzziness and uncertainty and the few examples that we can find are minority. To extend a popular system (which many of programmers are using) with this hability seems to be an interesting issue. Our first work (Fuzzy Prolog [1]) was a language that models B([0, 1])valued Fuzzy Logic. In the Borel Algebra, B([0, 1]), truth value is represented using unions of intervals of real numbers. It subsumed former approaches because it was more general in truth value representation and propagation than them. Now, we enhance our former approach by using default knowledge to represent incomplete information in Logic Programming. We also provide the implementation of this new framework. This new release of Fuzzy Prolog handles incomplete information and it has a complete semantics (the before one was incomplete as Prolog) which we discuss. New Fuzzy Prolog is more expressive to represent real world.
On the representation theorem of multiadjoint concept lattices
 IFSAEUSFLAT
, 2009
"... Formal concept analysis has become an important and appealing research topic. There exist a number of different fuzzy extensions of formal concept analysis and of its representation theorem, which gives conditions for a complete lattice in order to be isomorphic to a concept lattice. In this paper w ..."
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Formal concept analysis has become an important and appealing research topic. There exist a number of different fuzzy extensions of formal concept analysis and of its representation theorem, which gives conditions for a complete lattice in order to be isomorphic to a concept lattice. In this paper we concentrate on the study of operational properties of the mappings α and β required in the representation theorem.
Information technologies synergy of theory and application ⋆
"... In this lecture we give several examples and lessons learned from research, development and experiments in the area of theory and applications of information technology. We will try to describe a possible synergy of theory and application too. Namely, to describe where practical needs bring new prob ..."
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In this lecture we give several examples and lessons learned from research, development and experiments in the area of theory and applications of information technology. We will try to describe a possible synergy of theory and application too. Namely, to describe where practical needs bring new problems for theory and where theory helps to formulate methods, which should be verified in practice. In the theoretical part we will mention research on correctness and completeness of fuzzy logic programming [1,2] and various measures for evaluating success. In applications we mention acquaintance with development and experiments of preferential querying and user dependent topk answers [3]. In all of these it also depends on whether our task is deductive (querying),