Semantic Web Rules for Business Information

A. Maclachlan and H. Boley (Canada)

Keywords

Web knowledge bases. Data mining. Rulebased reason ing. Taxonomy alignment. Semantic Web rules. RuleML.

Abstract

A description of the New Brunswick Business Knowl edge Base (NBBizKB) is provided and is made available online in RuleML. NBBizKB realizes a two-step design. First, business facts are extracted, once from static CSV ta bles and, repeatedly from dynamic semi-structured HTML pages. Second, Semantic Web rules are developed to de rive information implicit in the fact base. Fact extraction comprises an XML DTD design, CSV-to-XML conversion, HTML mining, and XSLT translations. Rule derivation employs the Java-based RuleML implementation of OO jDREW to perform data validation, classification mapping, and information integration. Quantitative rule derivation results and findings about the original business data are reported. This rule-based reasoning over extracted facts about New Brunswick business comprises both a case study in business information mining and a use case for Semantic Web rules.

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