Sinopsis
Inductive Databases and Constraint-based Data Mining: Introduction and Overview.- Representing Entities in the OntoDM Data Mining Ontology.- A Practical Comparative Study Of Data Mining Query Languages.- A Theory of Inductive Query Answering.- Constraint-based Mining: Selected Techniques.- Generalizing Itemset Mining in a Constraint Programming Setting.- From Local Patterns to Classification Models.- Constrained Predictive Clustering.- Finding Segmentations of Sequences.- Mining Constrained Cross-Graph Cliques in Dynamic Networks.- Probabilistic Inductive Querying Using ProbLog.- Inductive Databases: Integration Approaches.- Inductive Querying with Virtual Mining Views.- SINDBAD and SiQL: Overview, Applications and Future Developments.- Patterns on Queries.- Experiment Databases.- Applications.- Predicting Gene Function using Predictive Clustering Trees.- Analyzing Gene Expression Data with Predictive Clustering Trees.- Using a Solver Over the String Pattern Domain to Analyze Gene Promoter Sequences.- Inductive Queries for a Drug Designing Robot Scientist.
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