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WEBI
2005
Springer
15 years 9 months ago
A Semi-Supervised Document Clustering Algorithm Based on EM
Document clustering is a very hard task in Automatic Text Processing since it requires to extract regular patterns from a document collection without a priori knowledge on the cat...
Leonardo Rigutini, Marco Maggini
129
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ICASSP
2009
IEEE
15 years 10 months ago
Experimenting with a global decision tree for state clustering in automatic speech recognition systems
In modern automatic speech recognition systems, it is standard practice to cluster several logical hidden Markov model states into one physical, clustered state. Typically, the cl...
Jasha Droppo, Alex Acero
ICIP
2005
IEEE
16 years 5 months ago
Fuzzy image segmentation of generic shaped clusters
Abstract The segmentation performance of any clustering algorithm is very sensitive to the features in an image, which ultimately restricts their generalization capability. This li...
Mohammed Ameer Ali, Gour C. Karmakar, Laurence S. ...
138
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CLOUD
2010
ACM
15 years 8 months ago
Comet: batched stream processing for data intensive distributed computing
Batched stream processing is a new distributed data processing paradigm that models recurring batch computations on incrementally bulk-appended data streams. The model is inspired...
Bingsheng He, Mao Yang, Zhenyu Guo, Rishan Chen, B...
140
Voted
CORR
2008
Springer
113views Education» more  CORR 2008»
15 years 3 months ago
Document stream clustering: experimenting an incremental algorithm and AR-based tools for highlighting dynamic trends
We address here two major challenges presented by dynamic data mining: 1) the stability challenge: we have implemented a rigorous incremental density-based clustering algorithm, i...
Alain Lelu, Martine Cadot, Pascal Cuxac