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Knowledge Discovery in Inductive Databases

5th International Workshop, KDID 2006 Berlin, Germany, September 18th, 2006 Revised Selected and Invited Papers

Saso Dzeroski, Jan Struyf (Herausgeber)

Buch | Softcover
X, 301 Seiten
2007 | 2007
Springer Berlin (Verlag)
978-3-540-75548-7 (ISBN)

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Knowledge Discovery in Inductive Databases -
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lt;p>This book constitutes the thoroughly refereed joint postproceedings of the 5th International Workshop on Knowledge Discovery in Inductive Databases, KDID 2006, held in association with ECML/PKDD. Bringing together the fields of databases, machine learning, and data mining, the papers address various current topics in knowledge discovery and data mining in the framework of inductive databases such as constraint-based mining, database technology and inductive querying.

Invited Talk.- Value, Cost, and Sharing: Open Issues in Constrained Clustering.- Contributed Papers.- Mining Bi-sets in Numerical Data.- Extending the Soft Constraint Based Mining Paradigm.- On Interactive Pattern Mining from Relational Databases.- Analysis of Time Series Data with Predictive Clustering Trees.- Integrating Decision Tree Learning into Inductive Databases.- Using a Reinforced Concept Lattice to Incrementally Mine Association Rules from Closed Itemsets.- An Integrated Multi-task Inductive Database VINLEN: Initial Implementation and Early Results.- Beam Search Induction and Similarity Constraints for Predictive Clustering Trees.- Frequent Pattern Mining and Knowledge Indexing Based on Zero-Suppressed BDDs.- Extracting Trees of Quantitative Serial Episodes.- IQL: A Proposal for an Inductive Query Language.- Mining Correct Properties in Incomplete Databases.- Efficient Mining Under Rich Constraints Derived from Various Datasets.- Three Strategies for Concurrent Processing of Frequent Itemset Queries Using FP-Growth.- Discussion Paper.- Towards a General Framework for Data Mining.

Erscheint lt. Verlag 7.11.2007
Reihe/Serie Information Systems and Applications, incl. Internet/Web, and HCI
Lecture Notes in Computer Science
Zusatzinfo X, 301 p.
Verlagsort Berlin
Sprache englisch
Maße 155 x 235 mm
Gewicht 480 g
Themenwelt Informatik Theorie / Studium Algorithmen
Schlagworte classification • Clustering • constraint-based mining • Database • Data Management • Data Mining • Hardcover, Softcover / Informatik, EDV/Informatik • HC/Informatik, EDV/Informatik • inductive databases • Knowledge Discovery • learning • machine learning • multi-objective regression • pattern mining • Query Languages • query optimization • Relational Database
ISBN-10 3-540-75548-9 / 3540755489
ISBN-13 978-3-540-75548-7 / 9783540755487
Zustand Neuware
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