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DATESO
2010
13 years 5 months ago
2010
Abstract. The high dimensionality of the data generated by social networks has been a big challenge for researchers. In order to solve the problems associated with this phenomenon,...
ISNN
2011
Springer
12 years 10 months ago
2011
Springer
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
VLDB
1999
ACM
1999
ACM
Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering
14 years 4 days ago
Many applications require the clustering of large amounts of high-dimensional data. Most clustering algorithms, however, do not work e ectively and e ciently in highdimensional sp...
TSMC
2002
13 years 7 months ago
2002
Abstract--This paper proposes a new algorithm for the reduction of the number of colors in an image. The proposed adaptive color reduction (ACR) technique achieves color reduction ...
EDBT
2012
ACM
11 years 10 months ago
2012
ACM
In this paper, we study how to find maximal k-edge-connected subgraphs from a large graph. k-edge-connected subgraphs can be used to capture closely related vertices, and findin...