Knowledge discovery in inductive databases

Autori

• Sas o. Dz eroski

Parametri

• Computer, IT, programmazione
• Lecture notes in computer science

Maggiori informazioni sul libro

InhaltsverzeichnisInvited 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.

Per saperne di più

Lingua: Inglese

Pubblicato: 2007

(In brossura)