Fuzzy Logic Programming

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https://hdl.handle.net/11705/PROLE/2019/FLP
Artículos en la categoría Fuzzy Logic Programming publicados en las Actas de las XIX Jornadas de Programación y Lenguajes (PROLE 2019).
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  • Miniatura
    Artículo
    Integrating WordNet into Bousi~Prolog
    Julián Iranzo, Pascual; Sáenz Pérez, Fernando. Actas de las XIX Jornadas de Programación y Lenguajes (PROLE 2019), 2019-09-02.
    In this paper we provide techniques to integrate WordNet into a Fuzzy Logic Programming System. Because WordNet relates words but does not give graded information of the relation between them, we have implemented standard similarity measures and new directives that allow us to generate the proximity equations linking two words with an approximation degree. Proximity equations are the key syntactic structures that, in addition to a weak unification algorithm, make possible a flexible query answering process in this kind of programming languages.
  • Miniatura
    Artículo
    Tuning Neural Networks in a Fuzzy Logic Programming Environment
    Moreno, Ginés; Pérez, Jesús; Riaza Valverde, José Antonio. Actas de las XIX Jornadas de Programación y Lenguajes (PROLE 2019), 2019-09-02.
    Wide datasets are usually used for training and validating neural networks, which can be later tuned in order to correct their behaviors according to a few number of test cases proposed by users. In this paper we show how the FLOPER system developed in our research group is able to perform this last task after coding a neural network with a fuzzy logic language where program rules extend the classical notion of clause by including on their bodies both fuzzy connectives (useful for modeling activation functions of neurons) and truth degrees (associated to weights and bias in neural networks). We present an online tool which helps to select such operators and values in an automatic way, accomplishing with our recent technique for tuning this kind of fuzzy programs. Moreover, we provide some experimental results revealing that our tool generates the choices that better fit user's preferences in a very efficient way, and producing relevant improvements on tuned neural networks.
  • Miniatura
    Resumen
    Tuning Fuzzy SPARQL Queries in a Fuzzy Logic Programming Environment
    Almendros-Jiménez, Jesus M.; Becerra Terón, Antonio; Moreno, Ginés; Riaza Valverde, José Antonio. Actas de las XIX Jornadas de Programación y Lenguajes (PROLE 2019), 2019-09-02.
    We have recently designed FSA-SPARQL, an extension of the SPARQL query language for querying fuzzy RDF datasets. Answers of FSA-SPARQL queries are usually annotated with truth degrees which are computed from fuzzy connectives and operators that act on truth degrees associated to RDF triples. While FSA-SPARQL offers a rich repertoire of fuzzy connectives and operators, it is not always easy to retrieve the user’s expected answers. This is very often due to wrong formulation of queries, caused by inadequate use/combination of fuzzy connectives, operators and thresholds. For instance, a high threshold for truth degrees in some RDF datasets can lead to an empty set of answers, some strong or weak restrictive combination of fuzzy conditions might produce few or too many answers, etc. On the other hand, our research group has also developed the fuzzy logic programming language FASILL, which has been equipped with tuning techniques for enabling the customization of queries from test cases. In this paper, our goals are: (1) to provide a FSA-SPARQL translation to FASILL and (2) apply the tuning techniques to FSA-SPARQL queries for getting more precise formulation of queries from test cases. Artículo pendiente de publicación en el 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2019): http://sites.ieee.org/fuzzieee-2019/