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IJIT
2004
13 years 7 months ago
IMDC: An Image-Mapped Data Clustering Technique for Large Datasets
In this paper, we present a new algorithm for clustering data in large datasets using image processing approaches. First the dataset is mapped into a binary image plane. The synthe...
Faruq A. Al-Omari, Nabeel I. Al-Fayoumi
MLDM
2005
Springer
13 years 11 months ago
Clustering Large Dynamic Datasets Using Exemplar Points
In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...
William Sia, Mihai M. Lazarescu
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
14 years 6 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
ICCS
2004
Springer
13 years 11 months ago
Visualization of Very Large Oceanography Time-Varying Volume Datasets
This paper presents two visualization techniques suitable for huge oceanography time-varying volume datasets on high-performance graphics workstations. We first propose an off-lin...
Sanghun Park, Chandrajit L. Bajaj, Insung Ihm
ICDCS
2006
IEEE
13 years 11 months ago
ParRescue: Scalable Parallel Algorithm and Implementation for Biclustering over Large Distributed Datasets
Biclustering refers to simultaneously capturing correlations present among subsets of attributes (columns) and records (rows). It is widely used in data mining applications includ...
Jianhong Zhou, Ashfaq A. Khokhar