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IEAAIE
2009
Springer
14 years 2 months ago
Incremental Mining of Ontological Association Rules in Evolving Environments
The process of knowledge discovery from databases is a knowledge intensive, highly user-oriented practice, thus has recently heralded the development of ontology-incorporated data ...
Ming-Cheng Tseng, Wen-Yang Lin
PAMI
2011
13 years 2 months ago
Action Recognition Using Mined Hierarchical Compound Features
—The field of Action Recognition has seen a large increase in activity in recent years. Much of the progress has been through incorporating ideas from single frame object recogn...
Andrew Gilbert, John Illingworth, Richard Bowden
BMCBI
2006
169views more  BMCBI 2006»
13 years 7 months ago
Finding biological process modifications in cancer tissues by mining gene expression correlations
Background: Through the use of DNA microarrays it is now possible to obtain quantitative measurements of the expression of thousands of genes from a biological sample. This techno...
Giacomo Gamberoni, Sergio Storari, Stefano Volinia
KDD
2005
ACM
161views Data Mining» more  KDD 2005»
14 years 7 months ago
Combining email models for false positive reduction
Machine learning and data mining can be effectively used to model, classify and discover interesting information for a wide variety of data including email. The Email Mining Toolk...
Shlomo Hershkop, Salvatore J. Stolfo
KDD
2002
ACM
140views Data Mining» more  KDD 2002»
14 years 7 months ago
Mining frequent item sets by opportunistic projection
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han