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» Techniques of Cluster Algorithms in Data Mining
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KDD
2007
ACM
176views Data Mining» more  KDD 2007»
16 years 7 months ago
Mining correlated bursty topic patterns from coordinated text streams
Previous work on text mining has almost exclusively focused on a single stream. However, we often have available multiple text streams indexed by the same set of time points (call...
Xuanhui Wang, ChengXiang Zhai, Xiao Hu, Richard Sp...
ICDE
2011
IEEE
217views Database» more  ICDE 2011»
14 years 10 months ago
Partitioning techniques for fine-grained indexing
— Many data-intensive websites use databases that grow much faster than the rate that users access the data. Such growing datasets lead to ever-increasing space and performance o...
Eugene Wu 0002, Samuel Madden
ICANN
2009
Springer
15 years 11 months ago
A Two Stage Clustering Method Combining Self-Organizing Maps and Ant K-Means
This paper proposes a clustering method SOMAK, which is composed by Self-Organizing Maps (SOM) followed by the Ant K-means (AK) algorithm. The aim of this method is not to find an...
Jefferson R. Souza, Teresa Bernarda Ludermir, Lean...
SDM
2012
SIAM
208views Data Mining» more  SDM 2012»
13 years 9 months ago
Mining Massive Archives of Mice Sounds with Symbolized Representations
Many animals produce long sequences of vocalizations best described as “songs.” In some animals, such as crickets and frogs, these songs are relatively simple and repetitive c...
Jesin Zakaria, Sarah Rotschafer, Abdullah Mueen, K...
FIMI
2003
120views Data Mining» more  FIMI 2003»
15 years 8 months ago
MAFIA: A Performance Study of Mining Maximal Frequent Itemsets
We present a performance study of the MAFIA algorithm for mining maximal frequent itemsets from a transactional database. In a thorough experimental analysis, we isolate the effec...
Douglas Burdick, Manuel Calimlim, Jason Flannick, ...