Semantic Web Rules for Business Information

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TypeArticle
ConferenceThe International Association of Science and Technology for Development (IASTED) International Conference on Web Technologies, Applications and Services (WTAS 2005), July 4-6, 2005., Calgary, Alberta, Canada
Subjectweb knowledge bases; data mining; rule-based reasoning; taxonomy alignment; semantic web rules; RuleML
AbstractA description of the New Brunswick Business Knowledge 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 tables and, repeatedly from dynamic semi-structured HTML pages. Second, Semantic Web rules are developed to derive 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.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number48263
NPARC number5764672
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Record identifier9ab82cf8-a372-4fa1-995b-ef2424a8117e
Record created2009-03-29
Record modified2016-05-09
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