Mario Lenz, Karl-Heinz Busch, André Hübner, and Stefan Wess
In this paper, we present details about the SIMATIC Knowledge Manager (SKM), a Textual CBR system that uses existing documents, such as FAQs and other useroriented documentation, and finds the most relevant documents for a given problem description. The major difference of the SKM compared to standard Information Retrieval tools and WWW search engines is that knowledge about the application domain can be brought into play when assessing the relevance of documents. Thus, not only the names of products, devices, and software components can be represented but also their relationships, such as dependencies between a series of products. Furthermore, the structure of the domain can be taken into account thus allowing a clustering of products into categories that express common properties. The SKM employs a case-based approach in that it considers the existing documents as cases and a user’s request as a query in the sense of the CBR paradigm. Also, by relying on these documents, a separate case authoring process is avoided which would require a substantial amount of both initial knowledge engineering when setting up the system as well as maintenance while the system is running.