59 research outputs found
Query Rewriting and Optimization for Ontological Databases
Ontological queries are evaluated against a knowledge base consisting of an
extensional database and an ontology (i.e., a set of logical assertions and
constraints which derive new intensional knowledge from the extensional
database), rather than directly on the extensional database. The evaluation and
optimization of such queries is an intriguing new problem for database
research. In this paper, we discuss two important aspects of this problem:
query rewriting and query optimization. Query rewriting consists of the
compilation of an ontological query into an equivalent first-order query
against the underlying extensional database. We present a novel query rewriting
algorithm for rather general types of ontological constraints which is
well-suited for practical implementations. In particular, we show how a
conjunctive query against a knowledge base, expressed using linear and sticky
existential rules, that is, members of the recently introduced Datalog+/-
family of ontology languages, can be compiled into a union of conjunctive
queries (UCQ) against the underlying database. Ontological query optimization,
in this context, attempts to improve this rewriting process so to produce
possibly small and cost-effective UCQ rewritings for an input query.Comment: arXiv admin note: text overlap with arXiv:1312.5914 by other author
Absolute Expressiveness of Subgraph-Based Centrality Measures
In graph-based applications, a common task is to pinpoint the most important or "central" vertex in a (directed or undirected) graph, or rank the vertices of a graph according to their importance. To this end, a plethora of so-called centrality measures have been proposed in the literature. Such measures assess which vertices in a graph are the most important ones by analyzing the structure of the underlying graph. A family of centrality measures that are suited for graph databases has been recently proposed by relying on the following simple principle: the importance of a vertex in a graph is relative to the number of "relevant" connected subgraphs surrounding it; we refer to the members of this family as subgraph-based centrality measures. Although it has been shown that such measures enjoy several favourable properties, their absolute expressiveness remains largely unexplored. The goal of this work is to precisely characterize the absolute expressiveness of the family of subgraph-based centrality measures by considering both directed and undirected graphs. To this end, we characterize when an arbitrary centrality measure is a subgraph-based one, or a subgraph-based measure relative to the induced ranking. These characterizations provide us with technical tools that allow us to determine whether well-established centrality measures are subgraph-based. Such a classification, apart from being interesting in its own right, gives useful insights on the structural similarities and differences among existing centrality measures
The Impact of Active Domain Predicates on Guarded Existential Rules
It is realistic to assume that a database management system provides access to the active domain via built-in relations. Therefore, databases that include designated predicates that hold the active domain, which we call product databases, form a natural notion that deserves our attention. An important issue then is to look at the consequences of product databases for the expressiveness and complexity of central existential rule languages. We focus on guarded-based existential rules, and we investigate the impact of product databases on their expressive power and complexity. We show that the queries expressed via (frontier-)guarded rules gain in expressiveness, and in fact, they have the same expressive power as Datalog. On the other hand, there is no impact on the expressiveness of the queries specified via weakly-(frontier-)guarded rules since they are powerful enough to explicitly compute the predicates needed to access the active domain. We also observe that there is no impact on the complexity of the query languages in question
All-Instances Restricted Chase Termination
The chase procedure is a fundamental algorithmic tool in database theory with
a variety of applications. A key problem concerning the chase procedure is
all-instances termination: for a given set of tuple-generating dependencies
(TGDs), is it the case that the chase terminates for every input database? In
view of the fact that this problem is undecidable, it is natural to ask whether
known well-behaved classes of TGDs ensure decidability. We consider here the
main paradigms that led to robust TGD-based formalisms, that is, guardedness
and stickiness. Although all-instances termination is well-understood for the
oblivious version of the chase, the more subtle case of the restricted (a.k.a.
the standard) chase is rather unexplored. We show that all-instances restricted
chase termination for guarded and sticky single-head TGDs is decidable
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