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Constraint-Based Mining and Inductive Databases

European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers

Specificaties
Paperback, 404 blz. | Engels
Springer Berlin Heidelberg | 2006e druk, 2006
ISBN13: 9783540313311
Rubricering
Springer Berlin Heidelberg 2006e druk, 2006 9783540313311
Onderdeel van serie Lecture Notes in Computer Science
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

The interconnected ideas of inductive databases and constraint-based mining are appealing and have the potential to radically change the theory and practice of data mining and knowledge discovery. This book reports on the results of the European IST project "cInQ" (consortium on knowledge discovery by Inductive Queries) and its final workshop entitled Constraint-Based Mining and Inductive Databases organized in Hinterzarten, Germany in March 2004.

Specificaties

ISBN13:9783540313311
Taal:Engels
Bindwijze:paperback
Aantal pagina's:404
Uitgever:Springer Berlin Heidelberg
Druk:2006

Inhoudsopgave

The Hows, Whys, and Whens of Constraints in Itemset and Rule Discovery.- A Relational Query Primitive for Constraint-Based Pattern Mining.- To See the Wood for the Trees: Mining Frequent Tree Patterns.- A Survey on Condensed Representations for Frequent Sets.- Adaptive Strategies for Mining the Positive Border of Interesting Patterns: Application to Inclusion Dependencies in Databases.- Computation of Mining Queries: An Algebraic Approach.- Inductive Queries on Polynomial Equations.- Mining Constrained Graphs: The Case of Workflow Systems.- CrossMine: Efficient Classification Across Multiple Database Relations.- Remarks on the Industrial Application of Inductive Database Technologies.- How to Quickly Find a Witness.- Relevancy in Constraint-Based Subgroup Discovery.- A Novel Incremental Approach to Association Rules Mining in Inductive Databases.- Employing Inductive Databases in Concrete Applications.- Contribution to Gene Expression Data Analysis by Means of Set Pattern Mining.- Boolean Formulas and Frequent Sets.- Generic Pattern Mining Via Data Mining Template Library.- Inductive Querying for Discovering Subgroups and Clusters.

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        Constraint-Based Mining and Inductive Databases