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...
Discovery of association rules is an important problem in database mining. In this paper we present new algorithms for fast association mining, which scan the database only once, ...
Mohammed Javeed Zaki, Srinivasan Parthasarathy, Mi...
This paper presents an autonomous algorithm for discovering exception rules from data sets. An exception rule, which is defined as a deviational pattern to a well-known fact, exhi...
In this paper, we employ a novel approach to metarule-guided, multi-dimensional association rule mining which explores a data cube structure. We propose algorithms for metarule-gu...