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ESANN
2007
15 years 5 months ago
Self-organized chains for clustering
This paper presents a new algorithm for clustering. It is an generalisation of the K-means algorithms . Each cluster will be represented by a chain of prototypes instead of being r...
Hassan Ghaziri
NIPS
2004
15 years 5 months ago
Efficient Out-of-Sample Extension of Dominant-Set Clusters
Dominant sets are a new graph-theoretic concept that has proven to be relevant in pairwise data clustering problems, such as image segmentation. They generalize the notion of a ma...
Massimiliano Pavan, Marcello Pelillo
PKDD
2007
Springer
109views Data Mining» more  PKDD 2007»
15 years 10 months ago
Matching Partitions over Time to Reliably Capture Local Clusters in Noisy Domains
Abstract. When seeking for small clusters it is very intricate to distinguish between incidental agglomeration of noisy points and true local patterns. We present the PAMALOC algor...
Frank Höppner, Mirko Böttcher
ICSE
1999
IEEE-ACM
15 years 8 months ago
Identifying Objects Using Cluster and Concept Analysis
Many approaches to support (semi-automatic) identification of objects in legacy code take the data structures as starting point for candidate classes. Unfortunately, legacy data ...
Arie van Deursen, Tobias Kuipers
DMIN
2006
120views Data Mining» more  DMIN 2006»
15 years 5 months ago
Time Series as a Point - A Novel Approach for Time Series Cluster Visualization
: Temporal data mining is concerned with the analysis of temporal data and finding temporal patterns, regularities, trends, clusters in sets of temporal data. Wavelet transform pro...
R. Pradeep Kumar, P. Nagabhushan