Naive Bayesian for Topic detection using "Bag of Words" approach

Posted by AlgoMan on Stack Overflow See other posts from Stack Overflow or by AlgoMan
Published on 2010-05-06T14:18:17Z Indexed on 2010/05/06 19:58 UTC
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bayesian

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machine-learning

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data-mining

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nlp

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natural-language

I am trying to implement a naive bayseian approach to find the topic of a given document or stream of words. Is there are Naive Bayesian approach that i might be able to look up for this ?

Also, i am trying to improve my dictionary as i go along. Initially, i have a bunch of words that map to a topics (hard-coded). Depending on the occurrence of the words other than the ones that are already mapped. And depending on the occurrences of these words i want to add them to the mappings, hence improving and learning about new words that map to topic. And also changing the probabilities of words.

How should i go about doing this ? Is my approach the right one ?

Which programming language would be best suited for the implementation ?

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