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SDM
2003
SIAM
125views Data Mining» more  SDM 2003»
13 years 11 months ago
Scalable, Balanced Model-based Clustering
This paper presents a general framework for adapting any generative (model-based) clustering algorithm to provide balanced solutions, i.e., clusters of comparable sizes. Partition...
Shi Zhong, Joydeep Ghosh
DKE
2006
125views more  DKE 2006»
13 years 9 months ago
Online clustering of parallel data streams
In recent years, the management and processing of so-called data streams has become a topic of active research in several fields of computer science such as, e.g., distributed sys...
Jürgen Beringer, Eyke Hüllermeier
KDD
2003
ACM
194views Data Mining» more  KDD 2003»
14 years 10 months ago
Finding recent frequent itemsets adaptively over online data streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Joong Hyuk Chang, Won Suk Lee
KDD
2010
ACM
233views Data Mining» more  KDD 2010»
14 years 1 months ago
Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora
Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
Jianwen Zhang, Yangqiu Song, Changshui Zhang, Shix...
KDD
2004
ACM
211views Data Mining» more  KDD 2004»
14 years 10 months ago
Towards parameter-free data mining
Most data mining algorithms require the setting of many input parameters. Two main dangers of working with parameter-laden algorithms are the following. First, incorrect settings ...
Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) R...