Stijn Heymans

Two-Phase Web Service Discovery Based on Rich Functional Descriptions

Discovery is a central reasoning task in service-oriented architectures, concerned with detecting Web services that are usable for solving a given request. This paper presents two extensions in continuation of previous works towards goal-based Web service discovery with sophisticated semantic matchmaking. At first, we distinguish goal templates as generic objective descriptions and goal instances that denote concrete requests as an instantiation of a goal template. Secondly, we formally describe requested and provided functionalities on the level of state transitions that denote executions of Web services, respectively solutions for goals. Upon this, we specify a two-phase discovery procedure along with semantic matchmaking techniques that allow to accurately determine the usability of a Web service. The techniques are defined in the Abstract State Space model that supports several languages for describing Web services.

Logical foundations of (e)RDF(S): complexity and reasoning

An important open question in the semantic Web is the precise relationship between the RDF(S) semantics and the semantics of standard knowledge representation formalisms such as logic programming and description logics. In this paper we address this issue by considering embeddings of RDF and RDFS in logic. Using these embeddings, combined with existing results about various fragments of logic, we establish several novel complexity results. The embeddings we consider show how techniques from deductive databases and description logics can be used for reasoning with RDF(S). Finally, we consider querying RDF graphs and establish the data complexity of conjunctive querying for the various RDF entailment regimes.

Nonmonotonic ontological and rule-based reasoning with extended conceptual logic programs

We present extended conceptual logic programs (ECLPs), for which reasoning is decidable and, moreover, can be reduced to finite answer set programming. ECLPs are useful to reason with both ontological and rule-based knowledge, which is illustrated by simulating reasoning in an expressive description logic (DL) equipped with DL-safe rules. Furthermore, ECLPs are more expressive in the sense that they enable nonmonotonic reasoning, a desirable feature in locally closed subareas of the Semantic Web.

Open answer set programming with guarded programs

Open answer set programming (OASP) is an extension of answer set programming where one may ground a program with an arbitrary superset of the programs constants. We define a fixed-point logic (FPL) extension of Clarks completion such that open answer sets correspond to models of FPL formulas and identify a syntactic subclass of programs, called (loosely) guarded programs. Whereas reasoning with general programs in OASP is undecidable, the FPL translation of (loosely) guarded programs falls in the decidable (loosely) guarded fixed-point logic (μ(L)GF). Moreover, we reduce normal closed ASP to loosely guarded OASP, enabling, for the first time, a characterization of an answer set semantics by μLGF formulas. We further extend the open answer set semantics for programs with generalized literals. Such generalized programs (gPs) have interesting properties, for example, the ability to express infinity axioms. We restrict the syntax of gPs such that both rules and generalized literals are guarded. Via a translation to guarded fixed-point logic, we deduce 2-EXPTIME-completeness of satisfiability checking in such guarded gPs (GgPs). Bound GgPs are restricted GgPs with EXPTIME-complete satisfiability checking, but still sufficiently expressive to optimally simulate computation tree logic (CTL). We translate Datalog lite programs to GgPs, establishing equivalence of GgPs under an open answer set semantics, alternation-free μGF, and Datalog LITE.

Guarded hybrid knowledge bases12

Recently, there has been a lot of interest in the integration of Description Logics (DL) and rules on the Semantic Web. We define guarded hybrid knowledge bases (or g-hybrid knowledge bases) as knowledge bases that consist of a Description Logic knowledge base and a guarded logic program, similar to the

Guarded open answer set programming

\mathcal{DL}

Semantic Web reasoning with Conceptual Logic Programs

+ log knowledge bases from Rosati (In Proceedings of the 10th International Conference on Principles of Knowledge Representation and Reasoning, AAAI Press, Menlo Park, CA, 2006, pp. 68–78.). g-Hybrid knowledge bases enable an integration of Description Logics and Logic Programming where, unlike in other approaches, variables in the rules of a guarded program do not need to appear in positive non-DL atoms of the body, i.e., DL atoms can act as guards as well. Decidability of satisfiability checking of g-hybrid knowledge bases is shown for the particular DL

Open answer set programming for the semantic web

\mathcal{DLRO}^{\-{le}}

Dealing with inconsistency when combining ontologies and rules using DL-Programs

, which is close to OWL DL, by a reduction to guarded programs under the open answer set semantics. Moreover, we show 2-Exptime-completeness for satisfiability checking of such g-hybrid knowledge bases. Finally, we discuss advantages and disadvantages of our approach compared with

Conceptual logic programs

\mathcal{DL}