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ICDM
2002
IEEE
122views Data Mining» more  ICDM 2002»
15 years 11 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
KDD
2006
ACM
123views Data Mining» more  KDD 2006»
16 years 7 months ago
Mining rank-correlated sets of numerical attributes
We study the mining of interesting patterns in the presence of numerical attributes. Instead of the usual discretization methods, we propose the use of rank based measures to scor...
Toon Calders, Bart Goethals, Szymon Jaroszewicz
KDD
2006
ACM
118views Data Mining» more  KDD 2006»
16 years 7 months ago
Mining for proposal reviewers: lessons learned at the national science foundation
In this paper, we discuss a prototype application deployed at the U.S. National Science Foundation for assisting program directors in identifying reviewers for proposals. The appl...
Seth Hettich, Michael J. Pazzani
ICDM
2008
IEEE
130views Data Mining» more  ICDM 2008»
16 years 1 months ago
Mining Temporal Patterns with Quantitative Intervals
In this paper we consider the problem of discovering frequent temporal patterns in a database of temporal sequences, where a temporal sequence is a set of items with associated da...
Thomas Guyet, Rene Quiniou
SDM
2011
SIAM
218views Data Mining» more  SDM 2011»
14 years 9 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