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» Why so many clustering algorithms: a position paper
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GECCO
2003
Springer
15 years 3 months ago
Mining Comprehensible Clustering Rules with an Evolutionary Algorithm
In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications. NOCEA evolves individuals that consist of a ...
Ioannis A. Sarafis, Philip W. Trinder, Ali M. S. Z...
ICDM
2006
IEEE
100views Data Mining» more  ICDM 2006»
15 years 3 months ago
Meta Clustering
Clustering is ill-defined. Unlike supervised learning where labels lead to crisp performance criteria such as accuracy and squared error, clustering quality depends on how the cl...
Rich Caruana, Mohamed Farid Elhawary, Nam Nguyen, ...
ICDE
2007
IEEE
148views Database» more  ICDE 2007»
15 years 11 months ago
Conquering the Divide: Continuous Clustering of Distributed Data Streams
Data is often collected over a distributed network, but in many cases, is so voluminous that it is impractical and undesirable to collect it in a central location. Instead, we mus...
Graham Cormode, S. Muthukrishnan, Wei Zhuang
ICDM
2007
IEEE
149views Data Mining» more  ICDM 2007»
15 years 4 months ago
Non-redundant Multi-view Clustering via Orthogonalization
Typical clustering algorithms output a single clustering of the data. However, in real world applications, data can often be interpreted in many different ways; data can have diff...
Ying Cui, Xiaoli Z. Fern, Jennifer G. Dy
IJNSEC
2010
112views more  IJNSEC 2010»
14 years 4 months ago
Detecting Connection-Chains: A Data Mining Approach
A connection-chain refers to a mechanism in which someone recursively logs into a host, then from there logs into another host, and so on. Connection-chains represent an important...
Ahmad Almulhem, Issa Traoré