Collaborative recommender systems are highly vulnerable to attack. Attackers can use automated means to inject a large number of biased profiles into such a system, resulting in r...
Robin D. Burke, Bamshad Mobasher, Chad Williams, R...
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
This paper describes ongoing work within the Aus-e-Lit project at the University of Queensland to provide collaborative annotation tools for Australian Literary Scholars. It descri...
Abstract. This paper reports our research work in the new field of humancomputer collaborative learning (HCCL). The general architecture of an HCCL is defined. An HCCL system, call...
The accuracy of detecting an intrusion within a network of intrusion detection systems (IDSes) depends on the efficiency of collaboration between member IDSes. The security itself ...
Carol J. Fung, Olga Baysal, Jie Zhang, Issam Aib, ...