Text mining in Python

Discussion in 'Python' started by mk, Mar 10, 2010.

  1. mk

    mk Guest

    Hello everyone,

    I need to do the following:

    (0. transform words in a document into word roots)

    1. analyze a set of documents to see which words are highly frequent

    2. detect clusters of those highly frequent words

    3. map the clusters to some "special" keywords

    4. rank the documents on clusters and "top n" most frequent words

    5. provide search that would rank documents according to whether search
    words were "special" cluster keywords or frequent words

    Is there some good open source engine out there that would be suitable
    to the task at hand? Anybody has experience with them?

    Now, I do now about NLTK and Python bindings to UIMA. The thing is, I do
    not know if those are good for the above task. If somebody has
    experience with those or other and would be able to say if they're good
    for this, please post.

    Regards,
    mk
     
    mk, Mar 10, 2010
    #1
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