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Ontology Driven Data Mining Satish Tadepalli Dept. Of Computer Science Virginia Tech A.K. Sinha Dept. Of Geo Sciences Virginia Tech Ontology-Driven Data Mining Data Mining: – Analysis of observational data sets to find unsuspected relationships and to summarize the data in novel ways Ontology – Represents domain knowledge – Relationships between concepts in a domain Ontology-driven data mining – Use the knowledge represented by ontologies to create a hierarchical structure in the data – Apply data mining techniques on the structured data sets GeoROC Database (http://georoc.mpch-mainz.gwdg.de/) GeoROC Data and Present Tectonic Setting Broad tectonic classification of GeoROC Data set for applying Data mining Techniques Classes · Convergent Margins · Continental Flood Basalts · Ocean Basin Flood Basalts · Ocean Island Groups · Ocean Island Plateaus · Others Subclasses (Location-based) · Tonga · New Zealand · Papua New Guinea · Central America · Others Attributes (Chemical/Isotope) · SiO2 · Al2O3 · MnO · Sr87/Sr86 · Others Structuring the data sets based on ontology Correlation Analysis Correlations in Continental Covergent Margins Correlations in Oceanic Convergent Margins 1 1 0.8 0.8 0.6 0.6 0.4 Si-K Si-Na2O Si-Fe 0.2 0 -0.2 Cascades Andean Both 0.4 0.2 0 -0.2 -0.4 -0.4 -0.6 -0.6 -0.8 -0.8 -1 -1 Tonga Mariana Both Si-K Si-Na2O Si-Fe Classification Using Neural Networks Present day Plate Tectonic settings and associated data are the key to recognizing paleo-tectonic settings of rocks. Ongoing Research Data mining of spatial data sets using Gaussian processes Sparse data mining Conclusion Ontology driven data mining – Meaningful patterns at multiple levels of abstraction – Multiple views of same data set – Ease in choosing the relevant data sets for comparison