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» Clustering by pattern similarity in large data sets
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MM
2005
ACM
146views Multimedia» more  MM 2005»
16 years 1 days 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
ESANN
2003
15 years 7 months ago
Semi-automatic acquisition and labelling of image data using SOMs
Abstract. Application of neural networks for real world object recognition suffers from the need to acquire large quantities of labelled image data. We propose a solution that acq...
Gunther Heidemann, Axel Saalbach, Helge Ritter
ICDAR
2009
IEEE
16 years 1 months ago
Unsupervised HMM Adaptation Using Page Style Clustering
In this paper we present an innovative two-stage adaptation approach for handwriting recognition that is based on clustering of similar pages in the training data. In our approach...
Huaigu Cao, Rohit Prasad, Shirin Saleem, Premkumar...
CGA
2006
15 years 6 months ago
The Distance-Similarity Metaphor in Region-Display Spatializations
n explore and understand abstract information spaces as if they were real geographic spaces. According to the distance-similarity metaphor1 one of the most popular spatial metaphor...
Sara Irina Fabrikant, Daniel R. Montello, David M....
LWA
2007
15 years 8 months ago
Multi-objective Frequent Termset Clustering
Large, high dimensional data spaces, are still a challenge for current data clustering methods. Frequent Termset (FTS) clustering is a technique developed to cope with these chall...
Andreas Kaspari, Michael Wurst