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MM
2005
ACM
146views Multimedia» more  MM 2005»
15 years 7 months ago
Unsupervised content discovery in composite audio
Automatically extracting semantic content from audio streams can be helpful in many multimedia applications. Motivated by the known limitations of traditional supervised approache...
Rui Cai, Lie Lu, Alan Hanjalic
KDD
2000
ACM
149views Data Mining» more  KDD 2000»
15 years 5 months ago
Efficient clustering of high-dimensional data sets with application to reference matching
Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
Andrew McCallum, Kamal Nigam, Lyle H. Ungar
PAA
2006
15 years 1 months ago
Efficient median based clustering and classification techniques for protein sequences
Abstract In this paper, an efficient K-medians clustering (unsupervised) algorithm for prototype selection and Supervised K-medians (SKM) classification technique for protein seque...
P. A. Vijaya, M. Narasimha Murty, D. K. Subramania...
AUSDM
2007
Springer
110views Data Mining» more  AUSDM 2007»
15 years 8 months ago
Useful Clustering Outcomes from Meaningful Time Series Clustering
Clustering time series data using the popular subsequence (STS) technique has been widely used in the data mining and wider communities. Recently the conclusion was made that it i...
Jason Chen
DEXAW
2009
IEEE
173views Database» more  DEXAW 2009»
15 years 8 months ago
Automatic Cluster Number Selection Using a Split and Merge K-Means Approach
Abstract—The k-means method is a simple and fast clustering technique that exhibits the problem of specifying the optimal number of clusters preliminarily. We address the problem...
Markus Muhr, Michael Granitzer