Attribute focusing: machine-assisted knowledge discovery applied to software production process control

Abstract How can people who are not trained in data analysis discover knowledge from a database of attribute-valued data? I address this question by presenting a man-machine approach to knowledge discovery called Attribute Focusing and its application to software production process control. Attribute Focusing utilizes an automatic filter to focus attention on that small part of a large amount of data which is interesting. A person studies that part in a manner which leads him to discover knowledge about the physical situation to which the data pertain. Specifically, the paper describes: 1. A model of interestingness of data based on the magnitude of data values, the association of data values and basic knowledge of the limits of human processing. 2. The use of that model of interestingness by people to discover knowledge. 3. The application of the Attribute Focusing approach to diagnose and correct the software production process. Based on the results that have been observed, the paper concludes that man-machine approaches to knowledge discovery should be emphasized much more than has been in the past, and that Attribute Focusing is a powerful, practical approach to such discovery.