Tracker: a framework to support reducing rework through decision management
Paul Rayson, Bernadette Sharp, Alan Alderson, John Cartmell, Claude C. Chibelushi, Rodney J. Clarke, Alan John Dix, Victor Onditi, Ariana Quek, Devina Ramduny-Ellis, Andrew M. Salter, Huma Shah, Ian Sommerville, Philip C. Windridge · Lancaster EPrints (Lancaster University) · 2003
The Tracker project is studying rework in systems engineering projects. Our hypothesis is that providing decision makers with information about previous relevant decisions will assist in reducing the amount of rework in a project. We propose an architecture for the flexible integration of the tools implementing the variety of theories and models used in the project. The techniques include ethnographic analysis, natural language processing, activity theory, norm analysis, and speech and handwriting recognition. In this paper, we focus on the natural language processing components, and describe experiments which demonstrate the feasibility of our text mining approach.