Extensive research for frequent-pattern mining in the past decade has brought forth a number of pattern mining algorithms that are both effective and efficient. However, the exist...
Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, H...
Frequent structure mining (FSM) aims to discover and extract patterns frequently occurring in structural data, such as trees and graphs. FSM finds many applications in bioinformat...
Interaction graphs are ubiquitous in many fields such as bioinformatics, sociology and physical sciences. There have been many studies in the literature targeted at studying and m...
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
Redescription mining is a newly introduced data mining problem that seeks to find subsets of data that afford multiple definitions. It can be viewed as a generalization of associa...