[Corpora-List] software for measuring semantic similarity and relatedness?

[Ted Pedersen]

Greetings all,

You can find the slides for the tutorial that came about with the help of
your responses. Thanks very much for your help in putting this together.

http://www.slideshare.net/duluthted/micai-2013tutorialpedersen

Like most things this is a work in progress, so any suggestions or comments
can certainly be included in the next iteration.

Cordially,
Ted



On Sun, Oct 6, 2013 at 10:45 AM, Ted Pedersen <tpederse at d.umn.edu> wrote:

> Greetings all,
>
> I'm preparing a tutorial on measuring semantic similarity and
> relatedness between concepts, My particular focus is on methods that
> do this using ontologies or other (at least somewhat) structured
> resources (like Wikipedia, folksonomies, etc.) and that also have
> freely available software associated with them (or at least a web
> demo).
>
> While it's a very interesting area, this particular tutorial won't
> include purely distributional approaches (due to time constraints), so
> I'm looking for methods and software that use some sort of resource
> like WordNet, Wikipedia, medical ontologies, Freebase, etc. to arrive
> at measurements of semantic similarity or relatedness between pairs of
> concepts.
>
> What follows is my current list, based not only on projects I have
> heard of but have used in the not too distant past - so I guess I'm
> particularly interested in projects you have used or created yourself
> (and can therefore vouch for to some extent).
>
> Based on WordNet, provide path, depth, info content based measures,
> may include relatedness measures like lesk, vector, hso
>
> WordNet::Similarity
> http://wn-similarity.sourcforge.net
>
> NLTK
> http://nltk.org
>
> ws4j
> https://code.google.com/p/ws4j/
>
> Based on UMLS (Unified Medical Language System), provide path, depth,
> info content measures, includes relatedness measures lesk, vector
>
> UMLS::Similarity
> http://umls-similarity.sourceforge.net
>
> Based on (GO), provide path, depth, and info content measures
>
> Proteinon
> http://lasige.di.fc.ul.pt/webtools/proteinon/
>
> I will post a summary of whatever I hear about after some period of
> time. Any hints or suggestions will be very gratefully received.
>
> Many thanks,
> Ted
>
> --
> Ted Pedersen
> http://www.d.umn.edu/~tpederse
>



-- 
Ted Pedersen
http://www.d.umn.edu/~tpederse
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