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DEXA
2001
Springer
151views Database» more  DEXA 2001»
13 years 9 months ago
Cache Conscious Clustering C3
The two main techniques of improving I/O performance of Object Oriented Database Management Systems(OODBMS) are clustering and buffer replacement. Clustering is the placement of o...
Zhen He, Alonso Marquez
CIDM
2009
IEEE
13 years 9 months ago
An architecture and algorithms for multi-run clustering
—This paper addresses two main challenges for clustering which require extensive human effort: selecting appropriate parameters for an arbitrary clustering algorithm and identify...
Rachsuda Jiamthapthaksin, Christoph F. Eick, Vadee...
INFOCOM
2002
IEEE
13 years 10 months ago
Clustering Overhead for Hierarchical Routing in Mobile Ad hoc Networks
Numerous clustering algorithms have been proposed that can support routing in mobile ad hoc networks (MANETs). However, there is very little formal analysis that considers the comm...
John Sucec, Ivan Marsic
ICDM
2002
IEEE
159views Data Mining» more  ICDM 2002»
13 years 10 months ago
O-Cluster: Scalable Clustering of Large High Dimensional Data Sets
Clustering large data sets of high dimensionality has always been a serious challenge for clustering algorithms. Many recently developed clustering algorithms have attempted to ad...
Boriana L. Milenova, Marcos M. Campos
ITNG
2010
IEEE
13 years 10 months ago
A Fast and Stable Incremental Clustering Algorithm
— Clustering is a pivotal building block in many data mining applications and in machine learning in general. Most clustering algorithms in the literature pertain to off-line (or...
Steven Young, Itamar Arel, Thomas P. Karnowski, De...
IDA
2003
Springer
13 years 10 months ago
Fuzzy Clustering of Short Time-Series and Unevenly Distributed Sampling Points
This paper proposes a new clustering algorithm in the fuzzy-c-means family, which is designed to cluster time series and is particularly suited for short time series and those wit...
Carla S. Möller-Levet, Frank Klawonn, Kwang-H...
IDA
2003
Springer
13 years 10 months ago
Fuzzy Clustering Based Segmentation of Time-Series
The segmentation of time-series is a constrained clustering problem: the data points should be grouped by their similarity, but with the constraint that all points in a cluster mus...
János Abonyi, Balazs Feil, Sandor Z. N&eacu...
IBPRIA
2003
Springer
13 years 10 months ago
Incrementally Assessing Cluster Tendencies with a Maximum Variance Cluster Algorithm
A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the ...
Krzysztof Rzadca, Francesc J. Ferri
GECCO
2003
Springer
322views Optimization» more  GECCO 2003»
13 years 10 months ago
AntClust: Ant Clustering and Web Usage Mining
Abstract. In this paper, we propose a new ant-based clustering algorithm called AntClust. It is inspired from the chemical recognition system of ants. In this system, the continuou...
Nicolas Labroche, Nicolas Monmarché, Gilles...
IRAL
2003
ACM
13 years 10 months ago
Keyword-based document clustering
1 Document clustering is an aggregation of related documents to a cluster based on the similarity evaluation task between documents and the representatives of clusters. Terms and t...
Seung-Shik Kang