From run-time behavior to usage scenarios: an interaction-pattern mining approach
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
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CLENG01The design of virtual workplaces that can support virtual work processes has traditionally been either ad-hoc, or has been influenced by the virtual architecture or requirements engineering disciplines. The problem with these approaches is the difficulty in obtaining, and subsequently retaining and reusing, ready-made configurations of collaborative work processes. Such configurations naturally occur during the actual use of CVEs for conducting projects. Can we predict some elements of the evolution of a new collaborative process, based on similarities and analogies with processes formalised and supported before? Can we capture and utilise the evolutionary component in the workspace design process, so that we can provide better support to the developers of collaborative workspaces? The paper presents a new approach for supporting design and redesign of virtual workspaces, based on combining data mining techniques for refining lower level models with a reverse engineering cycle to create upper level models.