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- 240 creator achille-fokoue.
- 240 creator aditya-kalyanpur.
- 240 creator guotong-xie.
- 240 creator hanyu-li.
- 240 creator jing-mei.
- 240 creator shengping-liu.
- 240 creator yuan-ni.
- 240 creator yue-pan.
- 240 type InProceedings.
- 240 label "A Practical Approach for Scalable Conjunctive Query Answering on Acyclic EL+ Knowledge Base".
- 240 sameAs 240.
- 240 abstract "Conjunctive query answering for EL++ ontologies has recently drawn much attention, as the Description Logic EL++ captures the expressivity of many large ontologies in the biomedical domain and is the foundation for the OWL 2 EL profile. In this paper, we propose a practical approach for conjunctive query answering in a fragment of EL++, namely acyclic EL+, that supports role inclusions. This approach can be implemented with low cost by leveraging any existing relational database management system to do the ABox data completion and query answering. We conducted a preliminary experiment to evaluate our approach using a large clinical data set and show our approach is practical.".
- 240 hasAuthorList authorList.
- 240 hasTopic Semantic_Web.
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- 240 title "A Practical Approach for Scalable Conjunctive Query Answering on Acyclic EL+ Knowledge Base".
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- 241 creator james-hendler.
- 241 creator jesse-weaver.
- 241 type InProceedings.
- 241 label "Parallel Materialization of the Finite RDFS Closure for Hundreds of Millions of Triples".
- 241 sameAs 241.
- 241 abstract "In this paper, we consider the problem of materializing the complete finite RDFS closure in a scalable manner; this includes those parts of the RDFS closure that are often ignored such as literal generalization and container membership properties. We point out characteristics of RDFS that allow us to derive an embarrassingly parallel algorithm for producing said closure, and we evaluate our C/MPI implementation of the algorithm on a cluster with 128 cores using different-size subsets of the LUBM 10,000-university data set. We show that the time to produce inferences scales linearly with the number of processes, evaluating this behavior on up to hundreds of millions of triples. We also show the number of inferences produced for different subsets of LUBM10k. To the best of our knowledge, our work is the first to provide RDFS inferencing on such large data sets in such low times. Finally, we discuss future work in terms of promising applications of this approach including OWL2RL rules, MapReduce implementations, and massive scaling on supercomputers.".
- 241 hasAuthorList authorList.
- 241 hasTopic Semantic_Web.
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- 241 title "Parallel Materialization of the Finite RDFS Closure for Hundreds of Millions of Triples".
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- 251 creator guilin-qi.
- 251 creator jianfeng-du.
- 251 creator qiu-ji.
- 251 type InProceedings.
- 251 label "Goal-Directed Module Extraction for Explaining OWL DL Entailments".
- 251 sameAs 251.
- 251 abstract "Module extraction methods have proved to be effective in improving the performance of some ontology reasoning tasks, including finding justifications to explain why an entailment holds in an OWL DL ontology. However, the existing module extraction methods that compute a syntactic locality-based module for the sub-concept in a subsumption entailment, though ensuring the resulting module to preserve all justifications of the entailment, may be insufficient in improving the performance of finding all justifications. This is because a syntactic locality-based module is independent of the super-concept in a subsumption entailment and always contains all concept/role assertions. In order to extract smaller modules to further optimize finding all justifications in an OWL DL ontology, we propose a goal-directed method for extracting a module that preserves all justifications of a given entailment. Experimental results on large ontologies show that a module extracted by our method is smaller than the corresponding syntactic locality-based module, making the subsequent computation of all justifications more scalable and more efficient.".
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- 251 title "Goal-Directed Module Extraction for Explaining OWL DL Entailments".
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- 253 creator guilin-qi.
- 253 creator jeff-z-pan.
- 253 creator jianfeng-du.