Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
This paper describes a theoretical approach on data mining, information classifying and a global overview of our OntoExtractor application, concerning the analysis of incoming data...
Zhan Cui, Ernesto Damiani, Marcello Leida, Marco V...
We present similarity-based methods to cluster digital photos by time and image content. The approach is general, unsupervised, and makes minimal assumptions regarding the structu...
Matthew L. Cooper, Jonathan Foote, Andreas Girgens...
Appropriate use of group consensus on service consumers’ QoS opinions can improve web service discovery. Web service participants with different backgrounds or preferences may n...
Wei-Li Lin, Chi-Chun Lo, Kuo-Ming Chao, Nick Godwi...
We consider a networking subsystem for message–passing clusters that uses two unidirectional queues for data transfers between the network interface card (NIC) and the lower prot...