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» Watershed-Based Unsupervised Clustering
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MM
2005
ACM
146views Multimedia» more  MM 2005»
15 years 5 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
NN
2007
Springer
173views Neural Networks» more  NN 2007»
14 years 11 months ago
An enhanced self-organizing incremental neural network for online unsupervised learning
An enhanced self-organizing incremental neural network (ESOINN) is proposed to accomplish online unsupervised learning tasks. It improves the self-organizing incremental neural ne...
Shen Furao, Tomotaka Ogura, Osamu Hasegawa
SDM
2008
SIAM
176views Data Mining» more  SDM 2008»
15 years 1 months ago
A General Model for Multiple View Unsupervised Learning
Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang
90
Voted
WWW
2007
ACM
16 years 13 days ago
U-REST: an unsupervised record extraction system
In this paper, we describe a system that can extract record structures from web pages with no direct human supervision. Records are commonly occurring HTML-embedded data tuples th...
Yuan Kui Shen, David R. Karger
NN
2006
Springer
153views Neural Networks» more  NN 2006»
14 years 11 months ago
An incremental network for on-line unsupervised classification and topology learning
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Shen Furao, Osamu Hasegawa