Knowledge Discovery in Inductive Databases [electronic resource] : 5th International Workshop, KDID 2006 Berlin, Germany, September 18, 2006 Revised Selected and Invited Papers / edited by Sao Dʾeroski, Jan Struyf.
Tipo de material:
TextoSeries Lecture Notes in Computer Science, 4747Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007Descripción: X, 301 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783540755494Trabajos contenidos: SpringerLink (Online service)Tema(s): Computer science | Database management | Artificial intelligence | Computer Science | Database Management | Artificial Intelligence (incl. Robotics)Formatos físicos adicionales: Sin títuloClasificación CDD: 005.74 Clasificación LoC:QA76.9.D3Recursos en línea: de clik aquí para ver el libro electrónico 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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