Scalable highly expressive reasoner (SHER)

被引：20

作者：

Dolby, Julian ^{[1
]}

Fokoue, Achille ^{[1
]}

Kalyanpur, Aditya ^{[1
]}

Schonberg, Edith ^{[1
]}

Srinivas, Kavitha ^{[1
]}

机构：

[1] IBM TJ Watson Res Ctr, Hawthorne, NY 10532 USA

来源：

JOURNAL OF WEB SEMANTICS | 2009年 / 7卷 / 04期

关键词：

Scalable ontology reasoner; OWL; Summarization; Explanations;

D O I：

10.1016/j.websem.2009.05.002

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we describe scalable highly expressive reasoner (SHER), a breakthrough technology that provides semantic querying of large relational datasets using OWL ontologies. SHER relies on a unique algorithm based on ontology summarization and combines a traditional in-memory description logic reasoner with a database backed RDF Store to scale reasoning to very large Aboxes. In our latest experiments, SHER is able to do sound and complete conjunctive query answering up to 7 million triples in seconds, and scales to datasets with 60 million triples, responding to queries in minutes. We describe the SHER system architecture, discuss the underlying components and their functionality, and briefly highlight two concrete use-cases of scalable OWL reasoning based on SHER in the Health Care and Life Science space. The SHER system, with the source code, is available for download (free for academic use) at: http://www.alphaworks.ibm.com/tech/sher. (C) 2009 Elsevier B.V. All rights reserved.

引用

页码：357 / 361

页数：5