The 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
web knowledge bases; data mining; rule-based reasoning; taxonomy alignment; semantic web rules; RuleML
A 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.
The International Association of Science and Technology for Development (IASTED) International Conference on Web Technologies, Applications and Services (WTAS 2005) [Proceedings].