Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
There is an emerging trend in post-genome biology to study the collection of thousands of protein interaction pairs (protein interactome) derived from high-throughput experiments....
We present and empirically analyze a machine-learning approach for detecting intrusions on individual computers. Our Winnowbased algorithm continually monitors user and system beh...
In today's industry, the design of software tests is mostly based on the testers' expertise, while test automation tools are limited to execution of pre-planned tests on...
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...