A multi-agent system for collaborative bookmarking
Rushed Kanawati, Maria Malek · 2002
In this paper we describe a multi-agent system, called COWING that aims at enabling an organised group of people to share their results of information searching on the World Wide Web. Users normally save relevant sites they found in their private collections of bookmarks. The goal of the proposed system is to enable users to share their bookmarks, in an implicit, secure and effective way. By implicit we mean that users are not required to spend extra effort in order to use the system. Secure sharing refers to the capacity of each user to control who knows what about her/his own bookmark collections. Finally effectiveness is ensured by recommending users with relevant bookmarks that are computed by applying a distributed collaborative filtering algorithm. Recommended bookmarks are automatically inserted in the most appropriate bookmark folder in the user's local collection. When accessing a folder the user can evaluate (accept or reject) provided recommendations. Our system is a multi-agent system where each user is associated to an assistant agent, called a WING agent. A WING agent observes the user's behaviour when managing her/his own bookmark collection. It learns how the user classifies her/his bookmarks. A hybrid neural/case-based reasoning supervised classifier is used for this purpose. WING agents exchange bookmarks according to a defined collaboration protocol that protects associated users privacy.