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

Ted Pedersen tpederse at d.umn.edu
Sun Nov 17 22:45:15 UTC 2013 

Hi Francis,

Sorry for the delay in reply, but yes, I agree. I think we should work
on getting a somewhat centralized list for these sorts of data
sources. I think the following is a good possible home, and I'll do
some updating there in the near future. And of course, if anyone else
would like to the same that would be even better!

http://aclweb.org/aclwiki/index.php?title=Similarity_(State_of_the_art)

Cordially,
Ted

On Tue, Oct 29, 2013 at 9:06 PM, Francis Bond <bond at ieee.org> wrote:
> G'day,
>
> I think these summaries are great!  Have you considered adding them to
> the aclwiki?  I think it is a good place to make these widely
> available (I try to keep the Japanese corpora page up-to-date).
>
> On Wed, Oct 30, 2013 at 2:39 AM, manaal faruqui <manaalfar at gmail.com> wrote:
>> I have recently assembled (under  construction) a list of all the available
>> lexical semantic evaluation benchmarks that people have been using in their
>> research. Hope people will find it useful!
>>
>> http://www.cs.cmu.edu/~mfaruqui/suite.html
>>
>> Manaal
>>
>>
>> On Tue, Oct 29, 2013 at 2:54 PM, Ted Pedersen <tpederse at d.umn.edu> wrote:
>>>
>>> Thanks to all who responded to my request for information about freely
>>> available packages to compute semantic similarity and relatedness
>>> using some sort of ontology or structured resource.
>>>
>>> Below is my best attempt at a summary - I have tried to be accurate
>>> here, but please if I've errored in how something is described (or
>>> have messed up a URL) please do let me know. And of course, if there
>>> are additions that should be made to this list, I'd be more than happy
>>> to learn of those and include both in this list and in the tutorial
>>> that motivated my original request. And my sincere apologies if
>>> someone sent me something that isn't included here - as long as there
>>> was an implementation that could be downloaded or accessed via the
>>> web, I intended to include that here (so please don't hesitate to
>>> remind me).
>>>
>>> I've divided the responses up into three categories.
>>>
>>> 1) packages that provide a variety of measures (and normally include
>>> multiple measures that were developed by someone else, and then
>>> implemented by the package authors perhaps along with a few of their
>>> own measures)
>>>
>>> 2) implementations of specific measures
>>>
>>> 3) gold standard human similarity and relatedness judgements
>>>
>>> Note that 3) wasn't included in my original request, but came about as
>>> a result of asking about the first two, so I thought I would include
>>> that information as well.
>>>
>>> ================================================
>>> Systems that provide a variety of measures :
>>> ================================================
>>>
>>> Based on WordNet and include measures based on path length, depth,
>>> information content, and may include relatedness measures like lesk,
>>> vector, hso
>>>
>>> 1) WordNet::Similarity http://wn-similarity.sourceforge.net
>>>
>>> 2) NLTK http://nltk.org
>>>
>>> 3) ws4j https://code.google.com/p/ws4j/
>>>
>>> 4) DKPro https://code.google.com/p/dkpro-similarity-asl/ (also
>>> includes support for Wikipedia/Wikirelate, Wiktionary, openThesaurus,
>>> GermaNet)
>>>
>>> Based on various medical ontologies
>>>
>>> 1) UMLS::Similarity http://umls-similarity.sourceforge.net (based on
>>> Unified Medical Language System)
>>>
>>> 2) Proteinon http://lasige.di.fc.ul.pt/webtools/proteinon/ (based on
>>> Gene Ontology)
>>>
>>> Systems where the focus may be on other issues but that still include
>>> some support of semantic similarity and relatedness measures between
>>> words/concepts
>>>
>>> 1) Disco http://www.linguatools.de/disco/disco_en.html (co-occurrence
>>> / corpus based similarity, but also includes plug-in for ontologies in
>>> Protege)
>>>
>>> 2) Semilar http://semanticsimilarity.org/ (text to text similarity but
>>> also includes support for word to word similarity)
>>>
>>> =================================================
>>> Implementations of Specific measures :
>>> =================================================
>>>
>>> 1) UKB http://ixa2.si.ehu.es/ukb/ (graph based similarity and
>>> relatedness, using WordNet)
>>>
>>> 2) http://www.cs.columbia.edu/~weiwei/code.html#wmfvec (high
>>> dimensional approach using definitions from WordNet/Wiktionary)
>>>
>>> 3) http://olesk.com/#SemanticRelatedness (shortest path in weighted
>>> semantic network)
>>>
>>>
>>> ==============================================================================
>>> Gold Standard data sets with human similarity and relatedness judgements :
>>>
>>> ==============================================================================
>>>
>>> 1) Yang and Powers 2006 Verb Similarity Scores (130 pairs)
>>>
>>> http://david.wardpowers.info/Research/AI/papers/200601-GWC-VerbSimWN.pdf
>>>
>>> http://david.wardpowers.info/Research/AI/papers/200601-GWC-130verbpairs.txt
>>>
>>> 2) WordSimilarity 353 Test Collection
>>>
>>> http://www.cs.technion.ac.il/~gabr/resources/data/wordsim353/
>>>
>>> http://alfonseca.org/eng/research/wordsim353.html (divided into
>>> similarity and relatedness pairs)
>>>
>>> 3) Rubenstein and Goodenough (65 pairs) Miller and Charles (30 pair
>>> subset of RG)
>>>
>>> http://www.d.umn.edu/~tpederse/Data/rubenstein-goodenough-1965.txt
>>>
>>> http://www.d.umn.edu/~tpederse/Data/miller-charles-1991.txt
>>>
>>> 4) ConceptSim (sense annotated versions of MC,RG, and WordSim 353)
>>>
>>> http://www.seas.upenn.edu/~hansens/conceptSim/
>>>
>>> 5) Medical concepts from UMLS
>>>
>>> http://rxinformatics.umn.edu/SemanticRelatednessResources.html
>>>
>>> Four different data sets, one with 101 pairs, another made up of a
>>> subset of 30 of those (both rated for relatedness), annother with 566
>>> pairs rated for similarity, and another with 587 pairs rated for
>>> relatedness.
>>>
>>> ========================================================================
>>>
>>> So, that's what I have at this point. Additional contributions,
>>> clarifications, etc. are certainly welcomed!
>>>
>>> Cordially,
>>> Ted
>>>
>>> On Sun, Oct 6, 2013 at 10:50 AM, Ted Pedersen <tpederse at d.umn.edu> wrote:
>>> > Well I managed to misspell my own URL :)
>>> >
>>> > WordNet::Similarity
>>> > http://wn-similarity.sourceforge.net
>>> >
>>> > All the others appear to be correct.
>>> >
>>> > 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
>>>
>>>
>>>
>>> --
>>> Ted Pedersen
>>> http://www.d.umn.edu/~tpederse
>>>
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>>
>>
>>
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>
>
>
> --
> Francis Bond <http://www3.ntu.edu.sg/home/fcbond/>
> Division of Linguistics and Multilingual Studies
> Nanyang Technological University



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

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