TY - BOOK AU - Boulicaut,Jean-Fran�ois AU - Raedt,Luc De AU - Mannila,Heikki ED - SpringerLink (Online service) TI - Constraint-Based Mining and Inductive Databases: European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers T2 - Lecture Notes in Computer Science, SN - 9783540313519 AV - Q334-342 U1 - 006.3 23 PY - 2006/// CY - Berlin, Heidelberg PB - Springer Berlin Heidelberg KW - Computer science KW - Computers KW - Database management KW - Information storage and retrieval KW - Artificial intelligence KW - Pattern recognition KW - Computer Science KW - Artificial Intelligence (incl. Robotics) KW - Computation by Abstract Devices KW - Database Management KW - Information Storage and Retrieval KW - Pattern Recognition N1 - 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 UR - http://dx.doi.org/10.1007/11615576 ER -