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SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
14 years 25 days ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
MICCAI
2009
Springer
14 years 8 months ago
Nonparametric Mean Shift Functional Detection in the Functional Space for Task and Resting-state fMRI
In functional Magnetic Resonance Imaging (fMRI) data analysis, normalization of time series is an important and sometimes necessary preprocessing step in many widely used methods. ...
Jian Cheng, Feng Shi, Kun Wang, Ming Song, Jiefeng...
IJCNN
2008
IEEE
14 years 2 months ago
Two-level clustering approach to training data instance selection: A case study for the steel industry
— Nowadays, huge amounts of information from different industrial processes are stored into databases and companies can improve their production efficiency by mining some new kn...
Heli Koskimäki, Ilmari Juutilainen, Perttu La...
KDD
2012
ACM
200views Data Mining» more  KDD 2012»
11 years 10 months ago
Vertex neighborhoods, low conductance cuts, and good seeds for local community methods
The communities of a social network are sets of vertices with more connections inside the set than outside. We theoretically demonstrate that two commonly observed properties of s...
David F. Gleich, C. Seshadhri
ICDM
2006
IEEE
152views Data Mining» more  ICDM 2006»
14 years 1 months ago
Application of Graph-based Data Mining to Metabolic Pathways
We present a method for finding biologically meaningful patterns on metabolic pathways using the SUBDUE graph-based relational learning system. A huge amount of biological data t...
Chang Hun You, Lawrence B. Holder, Diane J. Cook