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OpenRuleBench: an analysis of the performance of rule engines
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International World Wide Web Conference archive
Proceedings of the 18th international conference on World wide web table of contents
Madrid, Spain
SESSION: Semantic/data web/session: semantic data management table of contents
Pages 601-610  
Year of Publication: 2009
ISBN:978-1-60558-487-4
Authors
Senlin Liang  State University of New York at Stony Brook, Stony Brook, NY, USA
Paul Fodor  State University of New York at Stony Brook, Stony Brook, NY, USA
Hui Wan  State University of New York at Stony Brook, Stony Brook, NY, USA
Michael Kifer  State University of New York at Stony Brook, Stony Brook, NY, USA
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

The Semantic Web initiative has led to an upsurge of the interest in rules as a general and powerful way of processing, combining, and analyzing semantic information. Since several of the technologies underlying rule-based systems are already quite mature, it is important to understand how such systems might perform on the Web scale. OpenRuleBench is a suite of benchmarks for analyzing the performance and scalability of different rule engines. Currently the study spans five different technologies and eleven systems, but OpenRuleBench is an open community resource, and contributions from the community are welcome. In this paper, we describe the tested systems and technologies, the methodology used in testing, and analyze the results.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Senlin Liang: colleagues
Paul Fodor: colleagues
Hui Wan: colleagues
Michael Kifer: colleagues