Metasearch and machine learning to optimise WWW searching

Abstract

AI methodologies and the application of ma- chine learning techniques to optimize services provided by existent internet search technologies is one way to control and manage the immense and ever-increasing volume of data published on the WWW. Users demand effective and efficient on-line information access in a way to reduce the information overload. In this paper we present a novel approach to achieve these objectives by generating information which is of a high recall quality - by reusing the output generated from major search engines and other previously developed systems; and of a high precision calibre - by generating specific user profiles after several interactions with the system. This paper discusses the techniques involved, as well as practical issues such as information reuse, evolvability, profile generation, and graphic user interfaces.