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KDD
1999
ACM
117views Data Mining» more  KDD 1999»
15 years 9 months ago
Identifying Distinctive Subsequences in Multivariate Time Series by Clustering
Most time series comparison algorithms attempt to discover what the members of a set of time series have in common. We investigate a di erent problem, determining what distinguish...
Tim Oates
CEC
2007
IEEE
15 years 8 months ago
Evolution of classification rules for comprehensible knowledge discovery
This article, which lies within the data mining framework, proposes a method to build classifiers based on the evolution of rules. The method, named REC (Rule Evolution for Classif...
Emiliano Carreno, Guillermo Leguizamón, Nea...
SDM
2008
SIAM
120views Data Mining» more  SDM 2008»
15 years 6 months ago
Spatial Scan Statistics for Graph Clustering
In this paper, we present a measure associated with detection and inference of statistically anomalous clusters of a graph based on the likelihood test of observed and expected ed...
Bei Wang, Jeff M. Phillips, Robert Schreiber, Denn...
ICDM
2002
IEEE
122views Data Mining» more  ICDM 2002»
15 years 9 months ago
Using Category-Based Adherence to Cluster Market-Basket Data
In this paper, we devise an efficient algorithm for clustering market-basket data. Different from those of the traditional data, the features of market-basket data are known to b...
Ching-Huang Yun, Kun-Ta Chuang, Ming-Syan Chen
SDM
2011
SIAM
218views Data Mining» more  SDM 2011»
14 years 7 months ago
Segmented nestedness in binary data
A binary matrix is fully nested if its columns form a chain of subsets; that is, any two columns are ordered by the subset relation, where we view each column as a subset of the r...
Esa Junttila, Petteri Kaski