Scalable Web Reasoning Using Logic Programming Techniques

Abstract

One of the key issues for the uptake of the Semantic Web idea is the availability of reasoning techniques that are usable on a large scale and that offer rich modelling capabilities by providing comprehensive coverage of the OWL language. In this paper we present a scalable extension of our ABox reasoning framework called DLog. DLog performs query-driven execution whereby the terminological part of the description logic knowledge base is converted into a Logic Program and the assertional facts are accessed dynamically from a database. The problem of instance retrieval is reduced to a series of instance checks over a set of individuals containing all solutions for the query. Such a superset is calculated by using static-code analysis on the generated program. We identify two kinds of parallelism within DLog execution: (1) the instances in the superset can be independently checked in parallel and (2) a specific instance check can be executed in parallel by specialising well-established techniques from Logic Programming. Moreover, for efficiency reasons, we propose to use a specialised abstract machine rather than relying on the more generic WAM execution model. We describe the architecture of a distributed framework in which the above mentioned techniques are integrated. We compare our results to existing approaches.

Cascading verification: an integrated method for domain-specific model checking

“…Lukácsy and Szeredi incorporate this algorithm into a reasoning system named DLog, which generates Prolog programs from first-order clauses [46]. Extensions to DLog introduce optimization techniques including partial evaluation, which avoids the execution of unary predicates with uninstantiated arguments [85]; and parallel query execution [86].…”