Artificial intelligence (AI) support for knowledge management in construction

Abstract

This study focus on the investigation of the opportunities on the application of established artificial intelligence (AI) tools and techniques for the elicitation and representation of knowledge. This has been achieved by initially reviewing the development of knowledge management and artificial intelligence in general and also the context of construction industry. Case studies are used to show the situations of knowledge management systems in the construction organisations. From the results of the case studies and current researches, this report attempts to show the usefulness of deploying artificial intelligence tools and techniques in capturing and representation knowledge in the context of the construction industry. The study found protocol analysis and structure interview method are suitable to capture tacit knowledge (lessons learnt and best practices) in the construction organisations. In contrast, concept sorting method is appropriate tools to capture explicit knowledge. In the knowledge representation context, the combination of frames method and semantic network method are suitable to represent tacit knowledge (knowledge of people and processes). The Web-based technology also can be used to facilitate knowledge elicitation and representation in the construction organisations. In conclusion, all the above information are closely scrutinised and conclusions drawn that established artificial intelligence (AI) tools and techniques have significant effects in supporting end-users of knowledge management systems in construction industry context.