Logic and Learning on Databases

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Artículos en la categoría Logic and Learning on Databases publicados en las Actas de las XV Jornadas de Programación y Lenguajes (PROLE 2015).
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  • Artículo
    Restricted Predicates for Hypothetical Datalog
    Saenz-Perez, Fernando. Actas de las XV Jornadas de Programación y Lenguajes (PROLE 2015), 2015-09-15.
    Hypothetical Datalog is based on an intuitionistic semantics rather than on a classical logic semantics, and embedded implications are allowed in rule bodies. While the usual implication (i.e., the neck of a Horn clause) stands for inferring facts, an embedded implication plays the role of assuming its premise for deriving its consequence. A former work introduced both a formal framework and a goal-oriented tabled implementation, allowing negation in rule bodies. While in that work positive assumptions for both facts and rules can occur in the premise, negative assumptions are not allowed. In this work, we cover this subject by introducing a new concept: a restricted predicate, which allows negative assumptions by pruning the usual semantics of a predicate. This new setting has been implemented in the deductive system DES.
  • Artículo
    Learning a Subclass of Multivalued Dependencies Formulas from Entailments
    Hermo, Montserrat; Ozaki, Ana. Actas de las XV Jornadas de Programación y Lenguajes (PROLE 2015), 2015-09-15.
    Functional and multivalued dependencies play an important role in the design of relational databases. There is a strong connection between data dependencies and some fragments of the propositional logic. In particular, functional dependencies are closely related to Horn formulas. Also, multivalued dependencies are characterized in terms of multivalued formulas. It is known that both Horn formulas and sets of functional dependencies are efficiently learnable in the exact model of learning with queries. In this work, we study the learnability of a non-trivial subclass of multivalued formulas called CRMVDF. We use Angluin’s exact learning model with membership and equivalence queries and present a polynomial time algorithm which exactly learns CRMVDF from entailments.
  • Artículo
    HR-SQL: An SQL Database System with Extended Recursion and Hypothetical Reasoning
    Nieva, Susana; Saenz-Perez, Fernando; Sánchez-Hernández, Jaime. Actas de las XV Jornadas de Programación y Lenguajes (PROLE 2015), 2015-09-15.
    In a former work we described the system and language R-SQL that overcomes some limitations of recursion of the relational database language SQL. Such limitations are non-linearity, mutual recursion, and some combinations of negation with recursion. In addition, R-SQL improved termination properties of recursive definitions. Next, this language was extended to include a restricted form of hypothetical relations and queries using assumptions, obtaining the language HR-SQL, and a preliminary implementation was developed for it. Here, we develop a new system HR-SQL from scratch and enhance the former system in several areas. First, hypothetical reasoning is fully integrated with recursive definitions. Second, the Python script generated by the system for computing the extension (materialization) of a database is now targeted to several state-of-the-art relational database systems. Third, the system has been interfaced to the integrated development environment ACIDE, allowing both a more friendly user interaction and a graphical view of the dependency graph that shows dependencies between relations. Fourth, being developed in Prolog, we have targeted it to both SICStus Prolog and SWI-Prolog, also providing standalone executables. Finally, the system has been extended with a bundle of commands, highly improving its capabilities with respect to the former system.