Semantic similarity measurement gained attention over the last years as a non-standard inference service for various kinds of knowledge representations including description logics. Most existing similarity measures compute an undirected overall similarity, i.e., they do not take the context of the similarity query into account. If they do, the notion of context is usually reduced to the selection of particular concepts for comparison (instead of comparing all concepts within an examined ontology). The importance of context in deriving meaningful similarity judgments is beyond question and has been examined within recent research. This paper argues that there are several kinds of contexts. Each of them has its own impact on the resulting similarity values, but also on their interpretation. To support this view, the paper introduces definitions for the examined contexts and illustrates their influence by example.