Manydata mining algorithms developed recently are based on inductive learning methods. Very few are based on similarity-based learning. However, similarity-based learning accrues ...
Anapplication of data miningtechniques to heterogeneous database schemaintegration is introduced. We use attribute-oriented induction to minefor characteristic and classification ...
Random errors and insufficiencies in databases limit the performance of any classifier trained from and applied to the database. In this paper we propose a method to estimate the ...
Corinna Cortes, Lawrence D. Jackel, Wan-Ping Chian...
We introduce an active data mining paradigm that combines the recent work in data mining with the rich literature on active database systems. In this paradigm, data is continuousl...
For semantic query optimization one needs detailed knowledgeabout the contents of the database. Traditional techniquesuse static knowledgeabout all possible states of the database...
This paper introduces a newalgorithm called SIAO1 for learning first order logic rules withgenetic algorithms. SIAO1uses the covering principle developed in AQwhereseed examplesar...