Personalized support for learners becomes even more important, when e-Learning takes place in open and dynamic learning and information networks. This paper shows how to realize p...
Peter Dolog, Nicola Henze, Wolfgang Nejdl, Michael...
In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...
This paper presents our latest work on identifying frame content types for understanding learning media content. In particular, we categorize frames into six classes namely, slide...
Abstract. It has been recently demonstrated that the classical EM algorithm for learning Gaussian mixture models can be successfully implemented in a decentralized manner by resort...
Nikos A. Vlassis, Yiannis Sfakianakis, Wojtek Kowa...
We propose a new framework of explanation-oriented data mining by adding an explanation construction and evaluation phase to the data mining process. While traditional approaches c...