Machine learning typically involves discovering regularities in a training set, then applying these learned regularities to classify objects in a test set. In this paper we presen...
The success of the e-learning paradigm observed in recent times created a growing demand for e-learning systems in universities and other educational institutions, that itself led ...
Adaptive clustering uses external feedback to improve cluster quality; past experience serves to speed up execution time. An adaptive clustering environment is proposed that uses ...
Abraham Bagherjeiran, Christoph F. Eick, Chun-Shen...
Most studies in statistical or machine learning based authorship attribution focus on two or a few authors. This leads to an overestimation of the importance of the features extra...
Much research has been devoted to the study of exclusively distance-learning paradigms for teaching various technological subjects, yet many students have not been satisfied with ...