Tracker: a framework to support reducing rework through decision management |
||||
Paul Rayson2, Bernadette Sharp1, Albert Alderson1, John Cartmell11, Caroline Chibelushi1, Rodney Clarke1,3, Alan Dix2, Victor Onditi2, Amanda Quek1, Devina Ramduny2, Andy Salter1, Hanifa Shah1, Ian Sommerville2, Phil Windridge1 1 School of Computing, Staffordshire University, UK on the web: <@Tracker Project> <@paul> <@bernadette> < @rodney> <@alan> <@victor> <@devina> <@andy> <@hanifa> <@ian> |
||||
In 5th International Conference on Enterprise Information Systems (ICEIS 2003), Angers, France. |
|
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.
keywords: Decision management, rework, natural language processing, text mining