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» A Method for Dynamic Clustering of Data
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CORR
2008
Springer
113views Education» more  CORR 2008»
14 years 12 months ago
Document stream clustering: experimenting an incremental algorithm and AR-based tools for highlighting dynamic trends
We address here two major challenges presented by dynamic data mining: 1) the stability challenge: we have implemented a rigorous incremental density-based clustering algorithm, i...
Alain Lelu, Martine Cadot, Pascal Cuxac
SDMW
2004
Springer
15 years 5 months ago
Achieving Privacy Preservation when Sharing Data for Clustering
Abstract. In this paper, we address the problem of protecting the underlying attribute values when sharing data for clustering. The challenge is how to meet privacy requirements an...
Stanley R. M. Oliveira, Osmar R. Zaïane
ICDM
2006
IEEE
86views Data Mining» more  ICDM 2006»
15 years 6 months ago
Turning Clusters into Patterns: Rectangle-Based Discriminative Data Description
The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as human-comprehensible patterns from which end-users can gain intuiti...
Byron J. Gao, Martin Ester
ICASSP
2008
IEEE
15 years 6 months ago
Unsupervised validity measures for vocalization clustering
This paper describes unsupervised speech/speaker cluster validity measures based on a dissimilarity metric, for the purpose of estimating the number of clusters in a speech data s...
Kuntoro Adi, Kristine E. Sonstrom, Peter M. Scheif...
PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
15 years 9 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...