A Text Mining Approach to Tracking Elements of Decision Making: a pilot study

Understanding rework, the causes of rework, and the relationship between issues, decisions and the associated actions, is crucial in minimizing the fundamental industrial problems in system engineering projects. The aim of our research is to apply text mining techniques to track elements of decision making and extract semantic associations between decisions, actions and rework. Text mining is similar to data mining: while data mining seeks to discover meaningful patterns implicitly present in data, text mining aims to extract useful information and discovering semantic information hidden in texts. This paper describes work carried out as part of the first phase of our research, and investigates the effectiveness of using the text mining technique of lexical chains to identify important topics in transcribed texts. This research is part of the TRACKER research project which studies rework in system engineering projects.

• Type: Conference
• Year: 2004
• Where: NLUCS
• Authors: Caroline Chibelushi, Bernadette Sharp, Andy Salter
• Keywords: Data Mining, NLUCS 2004, NLUCS 2008, Text Mining, Text Mining Technique