Autor:
Moreno, Ginés

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gines.moreno@uclm.es

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Moreno

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Ginés

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Moreno, Gines

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Dep. of Computing Systems. U. of Castilla-La Mancha, Spain
University of Castilla-La Mancha, Spain
Universidad de Castilla-La Mancha
Department of Computing Systems University of Castilla-La Mancha
Dept. of Computing Systems University of Castilla-La Mancha 02071 Albacete (Spain)
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Mostrando 1 - 10 de 10
  • Artículo
    Introducing Fuzzy Quantifiers in FSA-SPARQL
    Almendros-Jiménez, Jesus M.; Becerra Terón, Antonio; Moreno, Ginés. Actas de las XXI Jornadas de Programación y Lenguajes (PROLE 2022), 2022-09-05.
    Fuzzy quantification makes it possible to model quantifiers from the natural language (most of, at least half, few, around a dozen, etc). Absolute quantifiers refer to a number while relative ones refer to a proportion. In this paper we introduce fuzzy quantifiers in FSA-SPARQL, a fuzzy extension of the SPARQL query language developed by our group. We focus on relative quantifiers (most of, at least half, few etc) and propose a fuzzy operator called QUANT to model relative fuzzy quantifiers in FSA-SPARQL. As in previous works about FSA-SPARQL, we study a translation of FSA-SPARQL queries involving fuzzy quantifiers to crisp SPARQL. The proposed extension has been implemented and it can be tested from the FSA-SPARQL Web site.
  • Artículo
    FSA-SPARQL: Fuzzy Queries in SPARQL
    Almendros-Jiménez, Jesus M.; Becerra Terón, Antonio; Moreno, Ginés. Actas de las XVII Jornadas de Programación y Lenguajes (PROLE 2017), 2017-07-19.
    SPARQL has been adopted as query language for the Semantic Web. RDF and OWL have been also established as vocabularies to describe ontologies in this setting. While RDF/OWL/SPARQL have been designed for querying crisp information, some contexts require to manage uncertainty, vagueness and imprecise knowledge. In this paper we propose a SPARQL extension, called FSA-SPARQL (Fuzzy Sets and Aggregators based SPARQL) in which queries can involve different fuzzy connectives and (aggregation) operators. The language has been implemented as an extension of the ARQ Jena SPARQL engine and it is equipped with a Web tool from which queries can be executed on-line.
  • Artículo
    Seeking a Safe and Efficient Similarity-based Unfolding Rule
    Julián Iranzo, Pascual; Moreno, Ginés; Riaza Valverde, José Antonio. Actas de las XX Jornadas de Programación y Lenguajes (PROLE 2021), 2021-09-22.
    The unfolding transformation has been widely used in many declarative frameworks for improving the efficiency of programs. Inspired by our previous experiences in fuzzy logic languages not dealing with similarity relations, in this work we try to adapt such operation to the so-called FASILL language (acronym of "Fuzzy Aggregators and Similarity Into a Logic Language") which has been developed in our research group for coping with implicit/explicit truth degree annotations, a great variety of connectives and unification by similarity. The traditional unfolding transformation is based on the application of unifiers on the heads and computational steps on the bodies of program rules. However, when considering similarity relations, the premature generation and application of weak (similarity-based) unifers at unfolding time could destroy the correctness of the transformation. In this paper we study how to avoid this risk by compiling what we call similarity constraints on transformed rules, whose further evaluation is delayed at running time. Moreover, our technique minimizes the size and number of occurrences of such constructs in transformed programs to gain efficiency while preserving semantics.
  • Artículo
    Fuzzy Thresholded Fixpoint Semantics
    Julián Iranzo, Pascual; Moreno, Ginés; Penabad, Jaime. Actas de las XVI Jornadas de Programación y Lenguajes (PROLE 2016), 2016-09-02.
    This work proposes an immediate consequences operator that allows us to give a fixpoint characterization of the least Herbrand model for a powerful class of fuzzy logic programs coping with implicit/explicit truth degree annotations, a great variety of connectives and unification by similarity. The so-called FASILL language (acronym of “Fuzzy Aggregators and Similarity Into a Logic Language”) has been recently designed and implemented in our research group and it enjoys the capability for managing filters or thresholds in a natural way in order to relax some computational and declarative aspects as revealed in the proposed fixpoint semantics.
  • Artículo
    A Declarative Semantics for a Fuzzy Logic Language Managing Similarities and Truth Degrees
    Julián Iranzo, Pascual; Moreno, Ginés; Penabad, Jaime; Vázquez, Carlos. Actas de las XV Jornadas de Programación y Lenguajes (PROLE 2015), 2015-09-15.
    This work proposes a declarative semantics based on a fuzzy variant of the classical notion of least Herbrand model for the so-called FASILL language (acronym of “Fuzzy Aggregators and Similarity Into a Logic Language”) which has being recently designed and implemented in our research group for coping with implicit/explicit truth degree annotations, a great variety of connectives and unification by similarity.
  • Artículo
    On the Safe Execution of Symbolic Similarity-based Fuzzy Logic Programs
    Moreno, Ginés; Riaza Valverde, José Antonio. Actas de las XXII Jornadas sobre Programación y Lenguajes (PROLE 2023), 2023-09-12.
    Introducing “Fuzzy Aggregators and Similarity Into a Logic Language” leads to FASILL, whose symbolic extension (called sFASILL) is able to manage both concrete and unknown (symbolic constants) truth degrees, similarity annotations and fuzzy connectives. The symbolic execution of sFASILL programs helps to guess the impact of such unknown symbols on the outputs before instantiating them with concrete values in program rules and similarity relations. In this paper we reason about the constraints that symbolic substitutions must satisfy in order to preserve the set of fuzzy computed answer obtained at execution time before or after instantiating a given sFASILL program. Based on such safeness conditions, we have formally proved two theoretical results with different levels of generality/practicability for correctly executing symbolic sFASILL and instantiated FASILL programs.
  • Artículo
    An Online Tool for Unfolding Symbolic Fuzzy Logic Programs (Demostración)
    Moreno, Ginés; Riaza Valverde, José Antonio. Actas de las XVIII Jornadas de Programación y Lenguajes (PROLE 2018), 2018-09-17.
    In many declarative frameworks, unfolding is a very well-known semantics-preserving transformation technique based on the application of computational steps on the bodies of program rules for improving efficiency. In this paper we describe an online tool which allows us to unfold a symbolic extension of a modern fuzzy logic language where program rules can embed concrete and/or symbolic fuzzy connectives and truth degrees on their bodies. The system offers a comfortable interaction with users for unfolding symbolic programs and it also provides useful options to navigate along the sequence of unfolded programs. Finally, the symbolic unfolding transformation is connected with some fuzzy tuning techniques that we previously implemented on the same tool.
  • Artículo
    Fuzzy Retrieval of Linked Open Data
    Almendros-Jiménez, Jesus M.; Becerra Terón, Antonio; Moreno, Ginés. Actas de las XXII Jornadas sobre Programación y Lenguajes (PROLE 2023), 2023-09-12.
    The technologies associated with the Semantic Web facilitate the publication of Open Data as well as their integration into the Linked Open Data cloud for which RDF format has been chosen. The promoted W3C RDF query language SPARQL became very popular and has been subject of study in recent years, with the goal of improving SPARQL engines in terms of functionality and usability. In this line of research, our research group has developed a fuzzy extension of SPARQL, called FSA-SPARQL (Fuzzy Sets and Aggregators based SPARQL). Here we go a step forward, adapting FSA-SPARQL for querying Linked Open Data with a fuzzy taste. Three goals are pursued, (i) fuzzification of Linked Open Data datasets, (ii) to extend FSA-SPARQL fuzzy aggregation and (iii) to equip FSA-SPARQL with quantification. Fuzzification, that is, interpretation of Linked Open Data datasets as fuzzy sets is made automatically at querying time, using trapezoidal membership functions. Powerful fuzzy aggregation and quantification operators are introduced in FSA-SPARQL based on fuzzy cardinals of fuzzy sets. As a result of the goals, FSA-SPARQL can be used for the retrieval of Linked Open Data datasets in real time, combining fuzzy aggregation and quantification. The proposed extension for FSA-SPARQL has been implemented and the system is available at our Web site.
  • 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.
  • Artículo
    Fuzzy Queries of Social Networks involving Sentiment Analysis and Topic Detection
    Almendros-Jiménez, Jesus M.; Becerra Terón, Antonio; Moreno, Ginés. Actas de las XVIII Jornadas de Programación y Lenguajes (PROLE 2018), 2018-09-17.
    Social networks have become a source of data which are of interest in all areas, and their querying and analysis is a hot topic in computer science. Our research group has developed a fuzzy extension of the Semantic Web query language SPARQL, called FSA-SPARQL (Fuzzy Sets and Aggregators based SPARQL). This extension provides mechanisms to express fuzzy queries against RDF data. FSA-SPARQL works with social networks. With this aim, FSA-SPARQL enables the transformation and fuzzification of social network API data. Fuzzification of social networks data is automatic and user-defined enabling a wide range of mechanisms for ranking and categorization, including sentiment analysis and topic detection. As case study, FSA-SPARQL has been used to query three well-known social networks: Twitter, Foursquare and TMDb.