Bottom-Up Association Rule Mining in Relational Databases
Journal of Intelligent Information Systems - Special issue on data warehousing and knowledge discovery
Logic-Based association rule mining in XML documents
APWeb'06 Proceedings of the 2006 international conference on Advanced Web and Network Technologies, and Applications
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Data mining from relational databases has recently become a popular way of discovering hidden knowledge. Methods such as association rules, chi square rules, ratio rules, implication rules, etc. that have been proposed in several contexts offer complimentary choices in rule induction in this model. Other than inductive and abductive logic programming, research into data mining from knowledge bases has been almost non-existent, because contemporary methods involve inherent procedurality which is difficult to cast into the declarativity of knowledge base systems. In this paper, we propose a logic-based technique for association rule mining from declarative knowledge which does not rely on procedural concepts such as candidate generation. This development is significant as this empowers the users with the capability to explore knowledge bases by mining association rules in a declarative and ad hoc fashion.