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A Parallel Reasoner for the Description Logic ALC
"... Abstract. Multi-processor/core systems have become ubiquitous but the vast majority of OWL reasoners can process ontologies only sequentially. This observation motivates our work on the design and evaluation of Deslog, a parallel tableau-based description logic reasoner for ALC. A first empirical ev ..."
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Cited by 8 (4 self)
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Abstract. Multi-processor/core systems have become ubiquitous but the vast majority of OWL reasoners can process ontologies only sequentially. This observation motivates our work on the design and evaluation of Deslog, a parallel tableau-based description logic reasoner for ALC. A first empirical evaluation for TBox classification demonstrates that Deslog’s architecture supports a speedup factor that is linear to the number of utilized processors/cores. 1
A self-organized semantic storage service
- In Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services (iiWAS2010), preprint available at http://digipolis.ag-nbi.de/preprint/iiwas2010-s4-preprint.pdf
, 2010
"... Abstract. Scalability requirements for semantic stores lead to distributed hardware-independent solutions to handle and analyze massive amounts of semantic data. We use a different approach by imitating the behaviour of swarm individuals to achieve this scalability. We have implemented our concept o ..."
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Cited by 6 (2 self)
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Abstract. Scalability requirements for semantic stores lead to distributed hardware-independent solutions to handle and analyze massive amounts of semantic data. We use a different approach by imitating the behaviour of swarm individuals to achieve this scalability. We have implemented our concept of a Self-organized Semantic Storage Service (S4) and present preliminary evaluation results in order to investigate to what extent the performance of a distributed and swarm-based storage system is dependent on its configuration. 1
Exploring Parallelization of Conjunctive Branches in Tableau-based Description Logic Reasoning
"... Abstract. Multiprocessor equipment is cheap and ubiquitous now, but users of description logic (DL) reasoners have to face the awkward fact that the major tableau-based DL reasoners can make use only one of the available processors. Recently, researchers have started investigating how concurrent com ..."
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Cited by 4 (3 self)
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Abstract. Multiprocessor equipment is cheap and ubiquitous now, but users of description logic (DL) reasoners have to face the awkward fact that the major tableau-based DL reasoners can make use only one of the available processors. Recently, researchers have started investigating how concurrent computing can play a role in tableau-based DL reasoning with the intention of fully exploiting the processing resources of multiprocessor computers. The published research mostly focuses on utilizing disjunctive branches, the or-part of tableau expansion trees. We investigated the possibility and the role of concurrently processing conjunctive branches, the and-part of tableau expansion trees. In this work, we present an algorithm to process conjunctive branches in parallel and address the key implementation aspects of the algorithm. A research prototype to execute this algorithm has been developed and empirically evaluated. The experimental results are presented and analyzed. We found that parallelizing the processing of conjunctive branches of tableau expansion trees is auspicious and can partly evolve into a scalable solution for DL reasoning. 1
Large-Scale Storage and Reasoning for Semantic Data Using Swarms
, 2012
"... The success of the Seman-tic Web leads to ever-growing amounts of data that are being generated, interlinked and consumed. Han-dling this massive volume is a serious challenge, where scalable, ..."
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The success of the Seman-tic Web leads to ever-growing amounts of data that are being generated, interlinked and consumed. Han-dling this massive volume is a serious challenge, where scalable,
Computing for the Semantic Web
"... Abstract The success of the Semantic Web, with the ever increasing publication of machine readable semantically rich data on the Web, has started to create serious problems as the scale and complexity of information outgrows the current methods in use, which are mostly based on database technology, ..."
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Abstract The success of the Semantic Web, with the ever increasing publication of machine readable semantically rich data on the Web, has started to create serious problems as the scale and complexity of information outgrows the current methods in use, which are mostly based on database technology, expressive knowledge representation formalism and high-performance computing. We argue that methods from computational intelligence (CI) can play an important role in solving these problems. In this paper we introduce and systemically discuss the typical application problems on the Semantic Web and discuss CI alternative to address the limitations of their underlying reasoning tasks consistently with respect to the increasing size, dynamicity and complexity of the data. Finally, we discuss two case studies in which we successfully applied soft computing methods to two of the main reasoning tasks; an evolutionary approach to querying, and a swarm algorithm for entailment. This short paper is a summary of Guéret, C.; Schlobach, S.; Dentler, K.; Schut, M.; Eiben, G. "Evolutionary and Swarm