Using Machine Learning to Enhance Software Tools for Internet Information Management

Abstract

This paper discusses the issues involved in the application of machine learning techniques to the management of Internet-based information. We present a general architecture, and describe how this has been instantiated in several different applications. The first three of these systems provide assistance to a user sorting incoming mail, reading USENET news or identifying World-Wide Web pages of interest; the final system constructs a personalised on-line newspaper, assembled from documents gathered by a Web robot. A number of machine learning techniques have been used in the construction of these systems; some comparative results are presented. Introduction The recent, rapid growth of the Internet has led to enormous amounts of on-line information. However, as the volume of this information has increased, so have the problems encountered by users in dealing with it. Interface agents have been proposed as a solution to this problem and can be characterised as systems which "employ Art...