Empirical evaluation of explicit versus implicit acquisition of user profiles in information filtering systems

Abstract

INTRODUCTION To make digital libraries attractive and encourage use, new and value-added services are needed beyond conventional distribution and access mechanisms. An exciting area of development is information personalization services that route, recommend, sort and prune documents (henceforth collectively called filtering) based on users’ interest profiles. Significant advances have been made in filtering systems. However, few studies have considered how different approaches of acquiring profiles can influence filtering effectiveness. Profiles are at the center of our research and one of the issues we are focussing in is profile acquisition by a filtering system that provides general health information.