Personalising Alerts with Bayesian Feed Filtering
Overview
We propose to develop and investigate the performance of a tool that will aggregate and filter a range of RSS and ATOM feeds selected by a user. The algorithm used for the filtering is similar to that used to identify spam in many email filters only in this case it will be "trained" to identify items that are interesting and should be highlighted, not those that should be junked. An important element of the project is investigating whether the filtering is effective enough to be helpful to users (specifically, in this case, researchers looking at journal tables of content for interesting newly-published papers) and disseminating information about the potential of this approach within the JISC community.
Lead Institution
