Spreading Activation algorithms are a well-known tool to determine relevance of nodes in a semantic network. Although often used, the configuration of a spreading activation algorithm is usually very problem-specific, and experience-driven. There are practically no guidelines or tools to help with the task. In this paper, we present semantic network skeletons, which are essentially a structural summary of a semantic network. We show how to derive the skeleton from a given semantic network, and

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... ow to derive conclusions about good configurations from it. Our results are then demonstrated in a case study from the automotive domain.