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11

ICDM
2003
IEEE

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OP-Cluster: Clustering by Tendency in High Dimensional Space

13 years 9 months ago

OP-Cluster: Clustering by Tendency in High Dimensional Space

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Clustering is the process of grouping a set of objects into classes of similar objects. Because of unknownness of the hidden patterns in the data sets, the deﬁnition of similarity is very subtle. Until recently, similarity measures are typically based on distances, e.g Euclidean distance and cosine distance. In this paper, we propose a ﬂexible yet powerful clustering model, namely OP-Cluster (Order Preserving Cluster). Under this new model, two objects are similar on a subset of dimensions if the values of these two objects induce the same relative order of those dimensions. Such a cluster might arise when the expression levels of (coregulated) genes can rise or fall synchronously in response to a sequence of environment stimuli. Hence, discovery of OP-Cluster is essential in revealing signiﬁcant gene regulatory networks. A deterministic algorithm is designed and implemented to discover all the signiﬁcant OP-Clusters. A set of extensive experiments has been done on several rea...

Jinze Liu, Wei Wang 0010

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Added	04 Jul 2010
Updated	04 Jul 2010
Type	Conference
Year	2003
Where	ICDM
Authors	Jinze Liu, Wei Wang 0010

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