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TIP
2010
97views more  TIP 2010»
14 years 11 months ago
Image Clustering Using Local Discriminant Models and Global Integration
In this paper, we propose a new image clustering algorithm, referred to as Clustering using Local Discriminant Models and Global Integration (LDMGI). To deal with the data points s...
Yi Yang, Dong Xu, Feiping Nie, Shuicheng Yan, Yuet...
COMPGEOM
2006
ACM
15 years 10 months ago
A fast k-means implementation using coresets
In this paper we develop an efficient implementation for a k-means clustering algorithm. The novel feature of our algorithm is that it uses coresets to speed up the algorithm. A ...
Gereon Frahling, Christian Sohler
SIGMOD
2007
ACM
186views Database» more  SIGMOD 2007»
16 years 4 months ago
An efficient and accurate method for evaluating time series similarity
A variety of techniques currently exist for measuring the similarity between time series datasets. Of these techniques, the methods whose matching criteria is bounded by a specifi...
Michael D. Morse, Jignesh M. Patel
PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
15 years 2 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
PRL
1998
132views more  PRL 1998»
15 years 4 months ago
Unsupervised feature selection using a neuro-fuzzy approach
A neuro-fuzzy methodology is described which involves connectionist minimization of a fuzzy feature evaluation index with unsupervised training. The concept of a ¯exible membersh...
Jayanta Basak, Rajat K. De, Sankar K. Pal