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This book is about inductive databases and constraint-based data mining, emerging research topics lying at the intersection of data mining and database research. The aim of the book as to provide an overview of the state-of- the art in this novel and - citing research area. Of special interest are the recent methods for constraint-based mining of global models for prediction and clustering, the uni?cation of pattern mining approaches through constraint programming, the clari?cation of the re- tionship between mining local patterns and global models, and the proposed in- grative frameworks and approaches for inducive databases. On the application side, applications to practically relevant problems from bioinformatics are presented. Inductive databases (IDBs) represent a database view on data mining and kno- edge discovery. IDBs contain not only data, but also generalizations (patterns and models) valid in the data. In an IDB, ordinary queries can be used to access and - nipulate data, while inductive queries can be used to generate (mine), manipulate, and apply patterns and models. In the IDB framework, patterns and models become ?rst-class citizens  and KDD becomes an extended querying process in which both the data and the patterns/models that hold in the data are queried.

Biomathematics. Biometry. Biostatistics --- Molecular biology --- Programming --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- datamining --- bio-informatica --- database management --- KI (kunstmatige intelligentie) --- moleculaire biologie --- data acquisition --- AI (artificiële intelligentie)

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Mathematical logic --- Complex analysis --- Operational research. Game theory --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- IR (information retrieval) --- stochastische analyse --- complexe analyse (wiskunde) --- machine learning --- database management --- informatietechnologie --- wiskunde --- logica --- robots