When analyzing the behavior of the LSA representation of <cite>(Gliozzo et al., 2005)</cite> we noticed that <cite>it captures</cite> two types of similarities between the category name and document terms. <cite>One type</cite> regards words which refer specifically to the category name's meaning, such as pitcher for the category Baseball. However, typical context words for the category which do not necessarily imply its specific meaning, like stadium, also come up as similar to baseball in LSA space. This limits <cite>the method's precision</cite>, due to false-positive classifications of contextually-related documents that do not discuss the specific category topic (such as other sports documents wrongly classified to Baseball). <cite>This behavior</cite> is quite typical for query expansion methods, which expand a query with contextually correlated terms. We propose a novel scheme that models separately these two types of similarity.