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ICUIMC
2009
ACM
16 years 27 days ago
PicAChoo: a tool for customizable feature extraction utilizing characteristics of textual data
Although documents have hundreds of thousands of unique words, only a small number of words are significantly useful for intelligent services. For this reason, feature extraction ...
Jaeseok Myung, Jung-Yeon Yang, Sang-goo Lee
ICDM
2008
IEEE
96views Data Mining» more  ICDM 2008»
16 years 25 days ago
Filling in the Blanks - Krimp Minimisation for Missing Data
Many data sets are incomplete. For correct analysis of such data, one can either use algorithms that are designed to handle missing data or use imputation. Imputation has the bene...
Jilles Vreeken, Arno Siebes
ICDM
2007
IEEE
149views Data Mining» more  ICDM 2007»
16 years 21 days ago
Temporal Analysis of Semantic Graphs Using ASALSAN
ASALSAN is a new algorithm for computing three-way DEDICOM, which is a linear algebra model for analyzing intrinsically asymmetric relationships, such as trade among nations or th...
Brett W. Bader, Richard A. Harshman, Tamara G. Kol...
ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
16 years 21 days ago
Incremental Subspace Clustering over Multiple Data Streams
Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
Qi Zhang, Jinze Liu, Wei Wang 0010
SSD
2005
Springer
173views Database» more  SSD 2005»
15 years 12 months ago
On Discovering Moving Clusters in Spatio-temporal Data
A moving cluster is defined by a set of objects that move close to each other for a long time interval. Real-life examples are a group of migrating animals, a convoy of cars movin...
Panos Kalnis, Nikos Mamoulis, Spiridon Bakiras