# Normalizing Term Frequency for document clustering

I have a problem understanding the normalization of Term Frequency weight in document Vector Space Model for clustering. Let's say that for document d I have counted occurences of all terms. I remember reading somewhere some time ago that they should be divided by maximum term frequency for that specific document, or sum of all frequencies, but I cannot find the source. Is that correct? If so, I would really appreciate getting some source for this information - I need it for my thesis. My second question is about calculating TF-IDF weight - in this case, should the TF be normalized somehow, or should I take 'raw' frequencies?