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Knowledge-intensive work plays an increasingly important role in organisations of all types. This work is characterized by a defined input and a defined output but not the way how to transform the input to an output. Within this context, the research project DYONIPOS aims at encouraging the two crucial roles in a knowledge-intensive organization - the process executer and the process engineer. Ad-hoc support will be provided for the knowledge worker by synergizing the development of context sensitive, intelligent, and agile semantic technologies with contextual retrieval. DYONIPOS provides process executers with guidance through business processes and just-in-time resource support based on the current user context, that are the focus of this paper.
We preset a network model for context-based retrieval allowing for integrating domain knowledge into document retrieval. Based on the premise that the results provided by a network model employing spreading activation are equivalent to the results of a vector space model, we create a network representation of a document collection for retrieval. We extended this well explored approach by blending it with techniques from knowledge representation. This leaves us with a network model for finding similarities in a document collection by content-based as well as knowledge-based similarities.
