A rough set-aided system for sorting WWW bookmarks

Abstract

Most people store ‘bookmarks’ to web pages. These allow the user to return to a web page later on, without having to remember the exact URL address. People attempt to organise their bookmark databases by filing bookmarks under categories, themselves arranged in a hierarchical fashion. As the maintenance of such large repositories is difficult and time-consuming, a tool that automatically categorises bookmarks is required. This paper investigates how rough set theory can help extract information out of this domain, for use in an experimental automatic bookmark classification system. In particular, work on rough set dependency degrees is applied to reduce the otherwise high dimensionality of the feature patterns used to characterize bookmarks. A comparison is made between this approach to data reduction and a conventional entropy-based approach.