A User Modeling Approach to Support Knowledge Work in Socio-computational Systems
The rise of socio-computational systems such as collaborative tagging systems, which rely heavily on user-generated content and social interactions, changed our way to learn and work. This work aims to explore the potentials of those systems for supporting knowledge work in organizational and scientific domains. Therefore, a user modeling approach will be developed which enables personalized services to shape the content towards individual information needs of novice, advanced and experienced knowledge workers. The novelty of this approach is a modeling strategy which combines user modeling characteristics from distinct research areas, the emergent properties of the socio-computational environment as well as non-invasive knowledge diagnosis methods based on the user’s past interaction with the system.
KeywordsUser modeling emergent semantics work-integrated learning personalized services collaborative tagging systems knowledge work
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