Both, the Vector Space Model (VSM) [Salton 1968; Baezea-Yates 1999, pp. 27-30] and the TVSM assign a document-vector to each document. In contrast to the TVSM the VSM assumes that all terms are independent (orthogonal) to each other. This leads to a relatively high performance. The assumption of orthogonal terms is incorrect regarding natural languages which causes problems with synonyms or strong related terms. In order to reduce these problems messages are usually passed through a stopword-list, stemming- and thesaurusalgorithms before they are forwarded to the VSM. This abrogates the assumption of term independence only in parts, because two terms can simply be treated as equivalent or as not equivalent. Similarity levels between these two extremes are not possible. From the theoretical point of view the TVSM has the advantage of not assuming independence for terms which allows a full integration of stopword-list, stemming and thesaurus into the model. Similarity between terms can be gradually defined from “not equivalent” (term-angle: 90°) to “equivalent” (term-angle: 0°).