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ICDE
1997
IEEE
130views Database» more  ICDE 1997»
14 years 8 months ago
High-Dimensional Similarity Joins
Many emerging data mining applications require a similarity join between points in a high-dimensional domain. We present a new algorithm that utilizes a new index structure, calle...
Kyuseok Shim, Ramakrishnan Srikant, Rakesh Agrawal
VLDB
2007
ACM
164views Database» more  VLDB 2007»
14 years 7 months ago
A new intrusion detection system using support vector machines and hierarchical clustering
Whenever an intrusion occurs, the security and value of a computer system is compromised. Network-based attacks make it difficult for legitimate users to access various network ser...
Latifur Khan, Mamoun Awad, Bhavani M. Thuraisingha...
ADMA
2006
Springer
110views Data Mining» more  ADMA 2006»
13 years 11 months ago
Learning with Local Drift Detection
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Gladys Castillo
IDA
2008
Springer
13 years 7 months ago
Symbolic methodology for numeric data mining
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
Boris Kovalerchuk, Evgenii Vityaev
EOR
2007
110views more  EOR 2007»
13 years 7 months ago
A hierarchical ant based clustering algorithm and its use in three real-world applications
In this paper is presented a new model for data clustering, which is inspired from the selfassembly behavior of real ants. Real ants can build complex structures by connecting the...
Hanene Azzag, Gilles Venturini, Antoine Oliver, Ch...