Constraint-Based Mining and Inductive Databases European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers / [electronic resource] :
edited by Jean-Francois Boulicaut, Luc De Raedt, Heikki Mannila.
- 1st ed. 2006.
- X, 404 p. online resource.
- Lecture Notes in Artificial Intelligence, 3848 2945-9141 ; .
- Lecture Notes in Artificial Intelligence, 3848 .
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.
9783540313519
10.1007/11615576 doi
Artificial intelligence. Computer science. Database management. Information storage and retrieval systems. Pattern recognition systems. Artificial Intelligence. Theory of Computation. Database Management. Information Storage and Retrieval. Automated Pattern Recognition.