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» Cascade Evaluation of Clustering Algorithms
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CEJCS
2011
78views more  CEJCS 2011»
13 years 11 months ago
Good versus optimal: Why network analytic methods need more systematic evaluation
: Network analytic method designed for the analysis of static networks promise to identify significant relational patterns that correlate with important structures in the complex ...
Katharina Anna Zweig
SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
15 years 12 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
ICDM
2007
IEEE
119views Data Mining» more  ICDM 2007»
15 years 6 months ago
Reducing UK-Means to K-Means
This paper proposes an optimisation to the UK-means algorithm, which generalises the k-means algorithm to handle objects whose locations are uncertain. The location of each object...
Sau Dan Lee, Ben Kao, Reynold Cheng
SIGIR
2002
ACM
14 years 11 months ago
Unsupervised document classification using sequential information maximization
We present a novel sequential clustering algorithm which is motivated by the Information Bottleneck (IB) method. In contrast to the agglomerative IB algorithm, the new sequential ...
Noam Slonim, Nir Friedman, Naftali Tishby
CINQ
2004
Springer
133views Database» more  CINQ 2004»
15 years 3 months ago
Inductive Querying for Discovering Subgroups and Clusters
We introduce the problem of cluster-grouping and show that it integrates several important data mining tasks, i.e. subgroup discovery, mining correlated patterns and aspects from c...
Albrecht Zimmermann, Luc De Raedt