# Concurrent Classification of EL Ontologies

@inproceedings{Kazakov2011ConcurrentCO,
title={Concurrent Classification of EL Ontologies},
author={Y. Kazakov and M. Kr{\"o}tzsch and F. Simancik},
booktitle={SEMWEB},
year={2011}
}
• Published in SEMWEB 2011
• Computer Science
We describe an optimised consequence-based procedure for classification of ontologies expressed in a polynomial fragment $${\mathcal{ELH_{R^+}}}$$ of the OWL 2 EL profile. A distinguishing property of our procedure is that it can take advantage of multiple processors/cores, which increasingly prevail in computer systems. Our solution is based on a variant of the ‘given clause’ saturation algorithm for first-order theorem proving, where we assign derived axioms to ‘contexts’ within which they… Expand
151 Citations
Goal-Directed Tracing of Inferences in EL Ontologies
• Computer Science
• Description Logics
• 2014
This paper presents a goal-directed method that can generate inferences for selected consequences in the deductive closure without re-applying all rules from scratch and provides an empirical evaluation demonstrating that the method is fast and economical for large $\mathcal{EL}$ ontologies. Expand
A Query Tool for EL with Non-monotonic Rules
• Computer Science
• SEMWEB
• 2013
The Protege plug-in NoHR is presented, that allows the user to take an $\mathcal{EL}^+_\top$ ontology, add a set of non-monotonic rules, and query the combined knowledge base, using the well-founded semantics for MKNF knowledge bases as underlying formalism. Expand
DESIGN AND EVALUATION OF ALGORITHMS FOR PARALLEL CLASSIFICATION OF ONTOLOGIES
The Parallel TBox Classifier is used to evaluate the practical merit of the proposed algorithms as well as the effectiveness of the designed optimizations against existing state-of-the-art benchmarks. Expand
A Divide and Conquer Approach for Parallel Classification of OWL Ontologies
• 2013
Description Logic (DL) describes knowledge using entities and relationships between them, and TBox classification is a core DL reasoning service. Over more than two decades many research efforts haveExpand
Incremental Reasoning in OWL EL without Bookkeeping
• Computer Science
• SEMWEB
• 2013
A technique for updating the classification of ontologies expressed in the $\mathcal{EL}$ family of Description Logics after some axioms have been added or deleted is described and its efficiency is demonstrated on naturally occurring and synthetic data. Expand
Consequence-Based Reasoning for Description Logics with Disjunctions and Number Restrictions
• Computer Science, Mathematics
• J. Artif. Intell. Res.
• 2018
The calculus and the techniques presented provide an important addition to the repertoire of practical implementation techniques for description logic reasoning, and are implemented in a new reasoner called Sequoia. Expand
Concurrent Classification of OWL Ontologies - An Empirical Evaluation
• Computer Science
• Description Logics
• 2012
The architecture of the research prototype and its employed algorithms were refactored by integrating lock-free data structures and adopting various optimizations to reduce overhead and the size of classified ontologies increased by one order of magnitude. Expand
Parallel OWL Reasoning: Merge Classification
• Computer Science
• JIST
• 2013
A novel algorithm is presented that uses a divide and conquer strategy for parallelizing OWL TBox classification, a key task in description logic reasoning, and a speedup of upi¾?to a factor of 4 has been observed when using 8 workers in parallel. Expand
A parallel computing architecture for high-performance OWL reasoning
• Computer Science
• Parallel Comput.
• 2019
This work presents a novel thread-level parallel architecture for ontology classification, which is ideally suited for shared-memory SMP servers, but does not rely on locking techniques and thus avoids possible race conditions. Expand
A Framework for Parallelizing OWL Classification in Description Logic Reasoners
• Computer Science
• ArXiv
• 2019
This thesis is the first to propose a flexible parallel framework which can be applied to existing OWL reasoners in order to speed up their classification process and demonstrates that the wall clock time of ontology classification can be improved by one order of the magnitude for most real-world ontologies in the repository. Expand

#### References

SHOWING 1-10 OF 29 REFERENCES
Parallel TBox Classification in Description Logics - First Experimental Results
• Computer Science
• ECAI
• 2010
This work on parallel TBox classification is extended and a new algorithm that is sound and complete is proposed and demonstrated in a first experimental evaluation a low overhead w.r.t. subsumption tests (less than 3%) if compared with sequential classification. Expand
Parallel Inferencing for OWL Knowledge Bases
• Computer Science
• 2008 37th International Conference on Parallel Processing
• 2008
This work examines the problem of parallelizing the inferencing process for OWL knowledge-bases with two approaches and presents an implementation based on a popular open source OWL reasoner and on a networked cluster. Expand
Distributed Resolution for Expressive Ontology Networks
• Computer Science
• RR
• 2009
A distributed reasoning method that preserves soundness and completeness of reasoning under the original OWL import semantics is proposed, based on resolution methods for $\mathcal{ALCHIQ}$ ontologies that are modified to work in a distributed setting. Expand
SAOR: Template Rule Optimisations for Distributed Reasoning over 1 Billion Linked Data Triples
• Computer Science
• SEMWEB
• 2010
The "partial-indexing" approach to scalable rule-based materialisation is generalised and reformalised, based on a separation of terminological data, to enable highly scalable and distributable reasoning for specific rulesets; in so doing, it provides some completeness propositions with respect to semi-naive evaluation. Expand
Parallelizing Tableaux-Based Description Logic Reasoning
• Computer Science
• OTM Workshops
• 2007
The approach for concurrent computation of the nondeterministic choices inherent to the standard tableau procedure is described and first promising performance results are presented when benchmarking the authors' prototypical reasoner UUPR (Ulm University Parallel Reasoner) with a selection of established DL systems. Expand
Experimental analysis of some computation rules in a simple parallel reasoning system for the ALC description logic
• A. Meissner
• Computer Science
• Int. J. Appl. Math. Comput. Sci.
• 2011
This paper empirically analyse three particular computation rules in a tableau-based, parallel reasoning system for the ALC description logic, which is built in the relational programming model in the Oz language. Expand
Parallelizing Description Logics
• Computer Science
• KI
• 1995
It is argued that object-level propagation is the most promising inference component for such a parallelization of DL algorithms, as opposed to normalization, comparison, or classification. Expand
Consequence-Based Reasoning beyond Horn Ontologies
• Mathematics, Computer Science
• IJCAI
• 2011
This paper presents a consequence-based procedure for ALCH that overcomes the difficulty of non-determinism in tableau-based procedures by using rules similar to ordered resolution to deal with disjunctive axioms in a deterministic way; it retains all the favourable attributes of existing consequence- based procedures. Expand
Parallel Materialization of the Finite RDFS Closure for Hundreds of Millions of Triples
• Computer Science
• SEMWEB
• 2009
This work is the first to provide RDFS inferencing on such large data sets in such low times and shows that the time to produce inferences scales linearly with the number of processes, evaluating this behavior on up to hundreds of millions of triples. Expand
Pushing the EL Envelope
• Mathematics, Computer Science
• IJCAI
• 2005
This work identifies a set of expressive means that can be added to EL without sacrificing tractability, and shows that basically all other additions of typical DL constructors to EL with GCIs make subsumption intractable, and in most cases even EXPTIME-complete. Expand