Using Formal Concept Analysis with an Incremental Knowledge Acquisition System for Web Document Management

Abstract

t is necessary to provide a method to store Web information effectively so it can be utilised as a future knowledge resource. A commonly adopted approach is to classify the retrieved information based on its content. A technique that has been found to be suitable for this purpose is Multiple Classification Ripple-Down Rules (MCRDR). The MCRDR system constructs a classification knowledge base over time using an incremental learning process. This incremental method of acquiring classification knowledge suits the nature of Web information because it is constantly evolving and being updated. However, despite this advantage, the classification knowledge of the MCRDR system is not often utilised for browsing the classified information. This is because it does not directly organise the knowledge in a way that is suitable for browsing. As a result, often an alternate structure is utilised for browsing the information which is usually based on a user's abstract understanding of the information domain. This study investigated the feasibility of utilising the classification knowledge acquired through the use of the MCRDR system as a resource for browsing information retrieved from the WWW. A system was implemented that used the concept lattice-based browsing scheme of Formal Concept Analysis (FCA) to support the browsing of documents based on the MCRDR classification knowledge. The feasibility of utilising classification knowledge as a resource for browsing documents was evaluated statistically. This was achieved by comparing the concept lattice-based browsing approach to a standard one that utilises abstract knowledge of a domain as a resource for browsing the same documents.