On the Convergence of Incremental Knowledge Base Construction.

Abstract. Ripple Down Rules is a practical methodology to build knowledgebased systems, which has proved successful in a wide range of commercial applications. However, little work has been done on its theoretical foundations. In this paper, we formalise the key features of the method. We present the process of building a correct knowledge base as a discovery scenario involving a user, an expert, and a system. The user provides data for classification. The expert helps the system to build its knowledge base incrementally, using the output of the latter in response to the last datum provided by the user. In case the system’s output is not satisfactory, the expert guides the system to improve its future performance while not affecting its ability to properly classify past data. We examine under which conditions the sequence of knowledge bases constructed by the system eventually converges to a knowledge base that faithfully represents the target classification function. Our results a...

• Type: Conference
• Year: 2004
• Where: DIS
• Authors: Tri M. Cao, Eric Martin, Paul Compton
• Keywords: Correct Knowledge Base, DIS 2004, Knowledge Base, Ripple Down Rules