Network equipments generate an overwhelming number of reports and alarms every day, but only a small fraction of these alarms require the intervention of network operators. Our goa...
Amelie Medem Kuatse, Renata Teixeira, Nicolas Usun...
In this paper, we propose a semi-supervised learning approach for classifying program (bot) generated web search traffic from that of genuine human users. The work is motivated by...
Hongwen Kang, Kuansan Wang, David Soukal, Fritz Be...
Abstract. This study presents a novel automatic approach for the identification of anatomical brain structures in magnetic resonance images (MRI). The method combines a fast multis...
Ayelet Akselrod-Ballin, Meirav Galun, Moshe John G...
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
This paper proposes a new approach for classifying text documents into two disjoint classes. The new approach is based on extracting patterns, in the form of two logical expressio...