Constraint-Based Mining and Inductive Databases: European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers: Lecture Notes in Computer Science, cartea 3848
Editat de Jean-Francois Boulicaut, Luc De Raedt, Heikki Mannilaen Limba Engleză Paperback – 25 ian 2006
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Specificații
ISBN-13: 9783540313311
ISBN-10: 3540313311
Pagini: 420
Ilustrații: X, 404 p.
Dimensiuni: 155 x 235 x 27 mm
Greutate: 0.59 kg
Ediția:2006
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3540313311
Pagini: 420
Ilustrații: X, 404 p.
Dimensiuni: 155 x 235 x 27 mm
Greutate: 0.59 kg
Ediția:2006
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
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.