Users of the World-Wide Web are not only confronted by an immense overabundance of information, but also by a plethora of tools for searching for the web pages that suit their inf...
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
We present a metadata free system for the interaction with massive collections of music, the MusicSurfer. MusicSurfer automatically extracts descriptions related to instrumentatio...
—In this paper, we describe and compare three Collaborative Filtering (CF) algorithms aiming at the low-rank approximation of the user-item ratings matrix. The algorithm implemen...
Manolis G. Vozalis, Angelos I. Markos, Konstantino...
Abstract. This paper describes an efficient method to construct reliable machine learning applications in peer-to-peer (P2P) networks by building ensemble based meta methods. We co...