Paper Info
Title
Exploration of SWRL Rule Bases through Visualization, Paraphrasing, and Categorization of Rules
Abstract
Rule bases are increasingly being used as repositories of knowledge content on the Semantic Web. As the size and complexity of these rule bases increases, developers and end users need methods of rule abstraction to facilitate rule management. In this paper, we describe a rule abstraction method for Semantic Web Rule Language (SWRL) rules that is based on lexical analysis and a set of heuristics. Our method results in a tree data structure that we exploit in creating techniques to visualize, paraphrase, and categorize SWRL rules. We evaluate our approach by applying it to several biomedical ontologies that contain SWRL rules, and show how the results reveal rule patterns within the rule base. We have implemented our method as a plug-in tool for Protégé-OWL, the most widely used ontology modeling software for the Semantic Web. Our tool can allow users to rapidly explore content and patterns in SWRL rule bases, enabling their acquisition and management.
Year
DOI
Venue
2009
10.1007/978-3-642-04985-9_23
RuleML
Keywords
Field
DocType
rule bases increase,swrl rule,categorize swrl rule,swrl rule base,rule abstraction method,rule base,rule pattern,swrl rule bases,rule abstraction,semantic web,rule management,lexical analysis,owl,semantic web rule language,data structure,knowledge representation,rule based
Data mining,Knowledge representation and reasoning,Rule-based system,Information retrieval,Open Biomedical Ontologies,Computer science,Semantic Web,Lexical analysis,Business rule management system,Semantic Web Rule Language,Database,Production Rule Representation
Conference
Volume
ISSN
Citations 
5858
0302-9743
7
PageRank 
References 
Authors
1.14
30
3
Name
Order
Citations
PageRank
Saeed Hassanpour1315.76
Martin J. O'Connor253657.50
Amar K. Das342051.09