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ICDM
2006
IEEE
139views Data Mining» more  ICDM 2006»
13 years 10 months ago
Unsupervised Clustering In Streaming Data
Tools for automatically clustering streaming data are becoming increasingly important as data acquisition technology continues to advance. In this paper we present an extension of...
Dimitris K. Tasoulis, Niall M. Adams, David J. Han...
SDM
2007
SIAM
187views Data Mining» more  SDM 2007»
13 years 6 months ago
Topic Models over Text Streams: A Study of Batch and Online Unsupervised Learning
Topic modeling techniques have widespread use in text data mining applications. Some applications use batch models, which perform clustering on the document collection in aggregat...
Arindam Banerjee, Sugato Basu
CORR
2010
Springer
138views Education» more  CORR 2010»
13 years 4 months ago
Data Stream Clustering: Challenges and Issues
Very large databases are required to store massive amounts of data that are continuously inserted and queried. Analyzing huge data sets and extracting valuable pattern in many appl...
Madjid Khalilian, Norwati Mustapha
ICPR
2008
IEEE
13 years 11 months ago
Unsupervised clustering using hyperclique pattern constraints
A novel unsupervised clustering algorithm called Hyperclique Pattern-KMEANS (HP-KMEANS) is presented. Considering recent success in semisupervised clustering using pair-wise const...
Yuchou Chang, Dah-Jye Lee, James K. Archibald, Yi ...
MM
2005
ACM
146views Multimedia» more  MM 2005»
13 years 10 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