Knowledge extraction and representation of collaborative activity through ontology-based and Social Network Analysis technologies

This paper describes an approach for extracting and representing the knowledge generated from collaborative interaction of small learning teams that work together in distance to carry out a software project or a case study. Our approach is based on ontology, Social Network Analysis (SNA) and fuzzy classification, which has been initially developed as a mechanism to analyse and understand behavioural patterns from collaboration performed in different scenarios. Through the SNA we are able to define an ontological profile that provides a deep knowledge about the participants' roles, intentions and effects; hence a fuzzy model can perform inferences over individual indicators. Copyright � 2009, Inderscience Publishers