Knowledge Discovery in Inductive Databases 5th International Workshop, KDID 2006 Berlin, Germany, September 18th, 2006 Revised Selected and Invited Papers /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Dzeroski, Saso (Editor ), Struyf, Jan (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2007.
Edición:1st ed. 2007.
Colección:Information Systems and Applications, incl. Internet/Web, and HCI ; 4747
Temas:
Data structures (Computer science).
Information theory.
Database management.
Artificial intelligence.
Data Structures and Information Theory.
Database Management.
Artificial Intelligence.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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