Probabilistic Relational Model Benchmark Generation

The validation of any database mining methodology goes through an evaluation process where benchmarks availability is essential. In this paper, we aim to randomly generate relational database benchmarks that allow to check probabilistic dependencies among the attributes. We are particularly interested in Probabilistic Relational Models (PRMs), which extend Bayesian Networks (BNs) to a relational data mining context and enable effective and robust reasoning over relational data. Even though a panoply of works have focused, separately , on the generation of random Bayesian networks and relational databases, no work has been identified for PRMs on that track. This paper provides an algorithmic approach for generating random PRMs from scratch to fill this gap. The proposed method allows to generate PRMs as well as synthetic relational data from a randomly generated relational schema and a random set of probabilistic dependencies. This can be of interest not only for machine learning researchers to evaluate their proposals in a common framework, but also for databases designers to evaluate the effectiveness of the components of a database management system

From ternary relationship to relational tables: a case against common beliefs

The transformation from n-ary relationships to a relational database schema has never been really fully analyzed. This paper presents one of the several ternary cases ignored by the ER-to-RM literature. The case shows that the following common belief is wrong: Given a set of FDs over a table resulting in a non-3NF situation, it is always possible to obtain a fully equivalent set of 3NF tables, without adding other restrictions than candidate keys and inclusion dependencies.Postprint (published version

Transforming N-ary relationships to database schemas: an old and forgotten problem

The N-ary relationships, have been traditionally a source of confusion and still are. One important source of confusion is that the term cardinality in a relationship has several interpretations, two of them being very popular. But none of the two approaches, nor the two together, allow us to express all the possible cardinality patterns. The transformations from all the possible relationships to database schemas have never been described by the existing literature. Using the 14 ternary patterns as example, we discuss these transformations particularly the transformations from the patterns ignored in the literature.Postprint (published version

Converting relational databases into object relational databases

This paper proposes an approach for migrating existing Relational DataBases (RDBs) into Object-Relational DataBases (ORDBs). The approach is superior to existing proposals as it can generate not only the target schema but also the data instances. The solution takes an existing RDB as input, enriches its metadata representation with required semantics, and generates an enhanced canonical data model, which captures essential characteristics of the target ORDB, and is suitable for migration. A prototype has been developed, which migrates successfully RDBs into ORDBs (Oracle 11g) based on the canonical model. The experimental results were very encouraging, demonstrating that the proposed approach is feasible, efficient and correct

Constraints for Semistructured Data and XML

Integrity constraints play a fundamental role in database design. We review initial work on the expression of integrity constraints for semistructured data and XML