  The proposed algorithmic approach deals with finding the sense of a word in
an electronic data. Now a day,in different communication mediums like internet,
mobile services etc. people use few words, which are slang in nature. This
approach detects those abusive words using supervised learning procedure. But
in the real life scenario, the slang words are not used in complete word forms
always. Most of the times, those words are used in different abbreviated forms
like sounds alike forms, taboo morphemes etc. This proposed approach can detect
those abbreviated forms also using semi supervised learning procedure. Using
the synset and concept analysis of the text, the probability of a suspicious
word to be a slang word is also evaluated.
