  Content based Document Classification is one of the biggest challenges in the
context of free text mining. Current algorithms on document classifications
mostly rely on cluster analysis based on bag-of-words approach. However that
method is still being applied to many modern scientific dilemmas. It has
established a strong presence in fields like economics and social science to
merit serious attention from the researchers. In this paper we would like to
propose and explore an alternative grounded more securely on the dictionary
classification and correlatedness of words and phrases. It is expected that
application of our existing knowledge about the underlying classification
structure may lead to improvement of the classifier's performance.
