I tried all the nltk methods for stemming but it gives me weird results with some words.
Examples
It often cut end of words when it shouldn\'t do it :
Stemming is all about removing suffixes(usually only suffixes, as far as I have tried none of the nltk stemmers could remove a prefix, forget about infixes). So we can clearly call stemming as a dumb/ not so intelligent program. It doesn't check if a word has a meaning before or after stemming. For eg. If u try to stem "xqaing", although not a word, it will remove "-ing" and give u "xqa".
So, in order to use a smarter system, one can use lemmatizers. Lemmatizers uses well-formed lemmas (words) in form of wordnet and dictionaries. So it always returns and takes a proper word. However, it is slow because it goes through all words in order to find the relevant one.