Title: Knowledge extraction and representation of collaborative activity through ontology-based and Social Network Analysis technologies
Authors: Luis Casillas, Thanasis Daradoumis
Addresses: Department of Computer Sciences, University of Guadalajara, Av. Revolucion, 1500, 44840 Guadalajara, Mexico. ' Department of Informatics, Multimedia and Telecommunications, Open University of Catalonia, Rambla Poblenou 156, 08018 Barcelona, Spain
Abstract: 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.
Keywords: collaboration; social networks; computer supported collaborative learning; ontology; CSCL; social network analysis; SNA; fuzzy classification; fuzzy modelling; small learning teams; knowledge extraction; knowledge representation.
International Journal of Business Intelligence and Data Mining, 2009 Vol.4 No.2, pp.141 - 158
Published online: 08 Jul 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article