Is this your question here, too?
http://stackoverflow.com/questions/17969532/how-to-normalize-similarity-measures-from-wordnet

On Wed, Mar 2, 2016 at 9:47 AM, 'AM' via Python Programming for Autodesk
Maya <[email protected]> wrote:

> I am trying to calculate semantic similarity between two words. I am using
> Wordnet-based similarity measures i.e Resnik measure(RES), Lin
> measure(LIN), Jiang, Conrath measure(JNC), and (LCH), but the similarity
> value is not between [0-1], So i need to normalize the similarity values as
> some measure give values between 0 and 1, while others give values greater
> than 1. even the word is similar or different.
>
> Code example:
>
> from nltk.corpus import wordnet as wn
>
> from nltk.corpus import wordnet_ic
>
> brown_ic = wordnet_ic.ic('ic-brown.dat')
>
> s1 = wordnet.synsets("car")
>
> s2 = wordnet.synsets("car")
>
> wn.wup_similarity(s1[0], s2[0])
>
> 1.0
>
> wn.lch_similarity(s1[0], s2[0])
>
> 3.6375861597263857
>
> wn.path_similarity(s1[0], s2[0])
>
> 1.0
>
> wn.jcn_similarity(s1[0], s2[0], brown_ic)
>
> 1e+300
>
> wn.res_similarity(s1[0], s2[0], brown_ic)
>
> 7.591401417609093
>
> wn.lin_similarity(s1[0], s2[0], brown_ic)
>
> 1.0
>
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