A Comparison of Data Sources for Machine Learning in a Telephone Trouble Screening Expert System

Abstract

This paper describes a domain where the application of machine learning, specifically inductive learning, could have enormous positive impact. The domain possesses attributes that would indicate that inductive learning would easily succeed for this domain. In particular, data for this domain are abundant. In spite of this, numerous machine learning methods -- both inductive and otherwise -- have failed to learn a knowledge base having high accuracy. This paper presents a comparison of the data sources available for this domain. It focuses primarily on a survey system that was ultimately designed for the purpose of collecting data best suited to this task. Keywords: knowledge acquisition for expert systems; knowledge elicitation; data collection; data collection interfaces This research was performed while the author was an employee of NYNEX Science and Technology, Inc. 1 Introduction Many machine learning techniques, most notably inductive methods, rely upon data from which they ..