A Fuzzy linguistic prolog and its applications

Rubio-Manzano, Clemente; Julián-Iranzo, Pascual

doi:10.3233/ifs-130834

Cited by 36 publications

(8 citation statements)

References 30 publications

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“…Bousi∼Prolog (BPL) [15,8] is a fuzzy logic programming language that replaces syntactic unification of classical SLD-resolution by a fuzzy unification algorithm. This algorithm provides a weak most general unifier and a corresponding unification degree (which takes a numeric value between 0 and 1).…”

Section: Integration Into Bousi∼prologmentioning

confidence: 99%

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WordNet and Prolog: why not?

Julián-Iranzo

Sáenz-Pérez

2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

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This paper describes a set of Prolog modules with predicates to access the information stored in the lexical database WordNet. The aim is to use the defined predicates for empowering (fuzzy) logic programming systems for approximate reasoning tasks. To achieve this goal it is necessary to have means to calculate the degree of relationship between the words. Because WordNet relates words but does not give graded information of the relation between those words, it is necessary to implement standard methods to compute that gradation.

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Section: Integration Into Bousi∼prologmentioning

confidence: 99%

“…(fuzzy) logic programming system implemented in Prolog. As an additional motivation for this work, we have incorporated this library into the Bousi∼Prolog fuzzy logic programming system [15,8] to facilitate approximate reasoning tasks and a more flexible query answering process.…”

Section: Introductionmentioning

confidence: 99%

WordNet and Prolog: why not?

Julián-Iranzo

Sáenz-Pérez

2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

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“…Also it is the first fuzzy logic programming language that proposed the use of proximity relations as a generalization of similarity relations [11]. It is worth saying that, in order to deal with proximity relations, Bousi∼Prolog has needed to develop new theoretical [14] and conceptual [28] basis.…”

Section: Introductionmentioning

confidence: 99%

“…Ending this section, it is important to say that our research group has been involved both on the development of similarity-based logic programming systems and those that extend the resolution principle, as reveals the design of the Bousi∼Prolog language 1 [11,13,28], where clauses cohabit with similarity/proximity equations, and the development of the FLOPER system 2 , which manages fuzzy programs composed by rules richer than clauses [20,23]. Our unifying approach is somehow inspired by [6], but in our framework we admit a wider set of connectives inside the body of programs rules.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Logic Programming Environment for Managing Similarity and Truth Degrees

Julián-Iranzo

Moreno

Penabad

et al. 2015

Electron. Proc. Theor. Comput. Sci.

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FASILL (acronym of "Fuzzy Aggregators and Similarity Into a Logic Language") is a fuzzy logic programming language with implicit/explicit truth degree annotations, a great variety of connectives and unification by similarity. FASILL integrates and extends features coming from MALP (Multi-Adjoint Logic Programming, a fuzzy logic language with explicitly annotated rules) and Bousi∼Prolog (which uses a weak unification algorithm and is well suited for flexible query answering). Hence, it properly manages similarity and truth degrees in a single framework combining the expressive benefits of both languages. This paper presents the main features and implementations details of FASILL. Along the paper we describe its syntax and operational semantics and we give clues of the implementation of the lattice module and the similarity module, two of the main building blocks of the new programming environment which enriches the FLOPER system developed in our research group.

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“…The main contribution of this paper is to design and implement an intervalvalued fuzzy logic language, and to incorporate it into the Bousi-Prolog system [15]. This task involves different challenges both from theoretical and implementation points of view.…”

mentioning

confidence: 99%

On the Incorporation of Interval-Valued Fuzzy Sets into the Bousi-Prolog System: Declarative Semantics, Implementation and Applications

Rubio-Manzano

Pereira-Fariña

2018

Studies in Computational Intelligence

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In this paper we analyse the benefits of incorporating interval-valued fuzzy sets into the Bousi-Prolog system. A syntax, declarative semantics and implementation for this extension is presented and formalised. We show, by using potential applications, that fuzzy logic programming frameworks enhanced with them can correctly work together with lexical resources and ontologies in order to improve their capabilities for knowledge representation and reasoning.

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A Fuzzy linguistic prolog and its applications

Cited by 36 publications

References 30 publications

WordNet and Prolog: why not?

WordNet and Prolog: why not?

A Fuzzy Logic Programming Environment for Managing Similarity and Truth Degrees

On the Incorporation of Interval-Valued Fuzzy Sets into the Bousi-Prolog System: Declarative Semantics, Implementation and Applications

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