This paper describes research focused on understanding the role of incomplete structural information about online collective action systems in participation decisions. Specificall...
On-line boosting is a recent advancement in the field of machine learning that has opened a new spectrum of possibilities in many diverse fields. With respect to a static strong...
Ingrid Visentini, Lauro Snidaro, Gian Luca Foresti
In huge online games where great numbers of players can be connected at the same time, social interaction is complex and conflicts become part of everyday life. There is a set of ...
The sales of customisable products and services over the internet is a challenging task within the area of electronic commerce. In this chapter we will present a case study which s...
Liliana Ardissono, Alexander Felfernig, Gerhard Fr...
This paper proposes an efficient online method that trains a classifier with many conjunctive features. We employ kernel computation called kernel slicing, which explicitly consid...