A Process Model for Developing Inductive Applications

A growing interest in real-world applications of inductive techniques signifies the need for methodologies for applying them. So far a number of methodologies for applying inductive learning techniques are described. After reviewing several published approaches, a number of unsolved problems are discussed, two major problems being the lackofattention to nontechnical issues and the focus of most approaches on specific, well defined problems with a limited scope. We propose the MeDIA-model as a reference structure for the application of inductive learning techniques that covers the issues mentioned in other approaches and generalises from problem specific approaches. The model is part of a methodology that aims at supporting the application of inductive learning techniques in various settings, and helps to plan projects where suchtechniques are involved

Introducing Inductive Methods in Knowledge Acquisition By Divide-and-Conquer

In this paper we present the outline of a method that combines a divide-and-conquer approach, that is common in knowledge acquisition and software engineering, with the use of inductive techniques. The idea is to guide decomposition of a knowledge acquisition problem into subpr oblems by the expected costs and benefits of applying elicitation or induction t o acquire the knowledge for part of the target knowledge. The method is illustra ted with a "rational reconstruction" of a knowledge acquisition process that involved inductive techniques. Keywords: Knowledge acquisition, learning goals, decomposition Introduction Knowledge acquisition for knowledge-based systems involves the formalisation of human knowledge about a certain task to build a system that can perform this task. Knowledge can be acquired in different ways. The classical way is to elicit knowledge from a human expert and formalise this in an operational language, e.g. using an expert system shell. This is often extende..