Item-based Collaborative Filtering (CF) algorithms have been designed to deal with the scalability problems associated with traditional user-based CF approaches without sacrificin...
act 11 Recommender systems anticipate users’ needs by suggesting items that are likely to interest them. Most existing systems 12 employ collaborative filtering (CF) techniques,...
Chris Cornelis, Jie Lu, Xuetao Guo, Guanquang Zhan...
This case study describes collaborative creativity in technology-supported teams with the task of making an interactive artefact. The teams work in the iLounge, which is designed a...
Abstract. This work proposes LEASE, a novel Mobile-P2P lease-based economic incentive model, in which data requestors need to pay the price (in virtual currency) of their requested...
A particularly challenging task for recommender systems (RSs) is deciding whether to recommend an item that received a variety of high and low scores from its users. RSs that inco...
Patricia Victor, Chris Cornelis, Martine De Cock, ...