1,721,064 research outputs found
An Extended Algebra for Constraints Databases
No full textConstraint relational databases use constraints to both model and query data. A constraint relation contains a finite set of generalized tuples. Each generalized tuple is represented by a conjunction of constraints on a given logical theory and, depending on the logical theory and the specific conjunction of constraints, it may possibly represent an infinite set of relational tuples. For their characteristics, constraint databases are well suited to model multidimensional and structured data, like spatial and temporal data. The definition of an algebra for constraint relational databases is important in order to make constraint databases a practical technology. We extend the previously defined constraint algebra (called generalized relational algebra). First, we show that the relational model is not the only possible semantic reference model for constraint relational databases and we show how constraint relations can be interpreted under the nested relational model. Then, we introduce two distinct classes of constraint algebras, one based on the relational algebra, and one based on the nested relational algebra, and we present an algebra of the latter type. The algebra is proved equivalent to the generalized relational algebra when input relations are modified by introducing generalized tuple identifiers. However, from a user point of view, it is more suitable. Thus, the difference existing between such algebras is similar to the difference existing between the relational algebra and the nested relational algebra, dealing with only one level of nesting. We also show how external functions can be added to the proposed algebr
Introducing cooperation and actions in amalgamated knowledge bases
No full textThe theory of amalgamated knowledge bases represents a formal logical foundation for heterogeneous databases. In an amalgamated knowledge base, data sources are modeled by generalized annotated logic. Moreover, an amalgamated knowledge base is equipped with a supervisor acting as a mediator for amalgamating knowledge from the local databases. Even if the framework is quite appealing, it does not model dynamic aspects. Moreover, no communication channels among local databases are supported and cooperation is provided only through the supervisor. In this paper, we extend the theory of amalgamated knowledge bases to deal with actions and cooperation among local database
Introducing dynamic behavior in amalgamated knowledge bases
No full textThe problem of integrating knowledge from multiple and heterogeneous sources is a fundamental issue in current information systems. To cope with this problem, the concept of mediator has been introduced as a software component providing intermediate services, linking data resources and application programs, and making transparent the heterogeneity of the underlying systems. In designing a mediator architecture, we believe that an important aspect is the definition of a formal framework by which one is able to model integration according to a declarative style. To this purpose, the use of a logical approach seems very promising. Another important aspect is the ability to model both static integration aspects, concerning query execution, and dynamic ones, concerning data updates and their propagation among the various data sources. Unfortunately, as far as we know, no formal proposals for logically modeling mediator architectures both from a static and dynamic point of view have already been developed. In this paper, we extend the framework for amalgamated knowledge bases, presented in Subrahmanian (1994), to deal with dynamic aspects. The language we propose is based on the Active U-Datalog language (Bertino et al., 1998), and extends it with annotated logic and amalgamation concepts from Kifer and Subrahmanian (1992) and Subrahmanian (1987). We model the sources of information and the mediator (also called supervisor) as Active U-Datalog deductive databases, thus modeling queries, transactions, and active rules, interpreted according to the PARK semantics (Gottlob et al., 1996). By using active rules, the system can efficiently perform update propagation among different databases. The result is a logical environment, integrating active and deductive rules, to perform queries and update propagation in an heterogeneous mediated framework
Enhancing the Expressive Power of the U-Datalog Language
No full textU-Datalog has been developed with the aim of providing a set-oriented logical update language, guaranteeing update parallelism in the context of a Datalog-like language. In U-Datalog, updates are expressed by introducing constraints (+p(X), to denote insertion, and -p(X), to denote deletion) inside Datalog rules. A U-Datalog program can be interpreted as a CLP program. In this framework, a set of updates (constraints) is satisfiable if it does not represent an inconsistent theory, that is, it does not require the insertion and the deletion of the same fact. This approach resembles a very simple form of negation. However, on the other hand, U-Datalog does not provide any mechanism to explicitly deal with negative information, resulting in a language with limited expressive power. In this paper, we provide a semantics, based on stratification, handling the use of negated atoms in U-Datalog programs, and we show which problems arise in defining a compositional semantics
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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