What online machine learning can do for knowledge acquisition—a case study

Abstract

This paper reports on the development of a realistic knowledge-based application using the MOBAL system. Some problems and requirements resulting from industrial-caliber tasks are formulated. A step-by-step account of the construction of a knowledge base for such a task demonstrates how the interleaved use of several learning algorithms in concert with an inference engine and a graphical interface can fulfill those requirements. Design, analysis, revision, refinement and extension of a working model are combined in one incremental process. This illustrates the balanced cooperative modelling approach. The case study is taken from the telecommunications domain and more precisely deals with security management in telecommunications networks. MOBAL would be used as part of a security management tool for acquiring, validating and refining a security policy. The modeling approach is compared with other approaches, such as KADS and stand-alone machine learning.