Siddharth Patwardhan > WordNet-Similarity-1.04

WordNet-Similarity-1.04

This Release WordNet-Similarity-1.04  [Download] [Browse 13 Dec 2006
Latest Release WordNet-Similarity-2.05  [Download] [Browse 16 Jun 2008
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Special Files
doc/changelog
doc/todo
INSTALL
Makefile.PL
MANIFEST
META.yml
README

Modules

WordNet::Similarity Perl modules for computing measures of semantic relatedness.     1.04
WordNet::Similarity::DepthFinder methods to find the depth of synsets in WordNet taxonomies     1.01
WordNet::Similarity::GlossFinder module to implement gloss finding methods for WordNet::Similarity measures of semantic relatedness (specifically, lesk and vector)     1.01
WordNet::Similarity::ICFinder a module for finding the information content of concepts in WordNet     1.03
WordNet::Similarity::PathFinder module to implement path finding methods (by node counting) for WordNet::Similarity measures of semantic relatedness     1.01
WordNet::Similarity::hso Perl module for computing semantic relatedness of word senses using the method described by Hirst and St-Onge (1998).     1.03
WordNet::Similarity::jcn Perl module for computing semantic relatedness of word senses according to the method described by Jiang and Conrath (1997).     1.01
WordNet::Similarity::lch Perl module for computing semantic relatedness of word senses using the method described by Leacock and Chodorow (1998).     1.03
WordNet::Similarity::lesk Perl module for computing semantic relatedness of word senses using gloss overlaps as described by Banerjee and Pedersen (2002) -- a method that adapts the Lesk approach to WordNet.     1.03
WordNet::Similarity::lin Perl module for computing semantic relatedness of word senses using the information content based measure described by Lin (1998).     1.01
WordNet::Similarity::path Perl module for computing semantic relatedness of word senses by counting nodes in the noun and verb WordNet 'is-a' hierarchies.     1.01
WordNet::Similarity::random Perl module for computing semantic relatedness of word senses using a random measure.     1.03
WordNet::Similarity::res Perl module for computing semantic relatedness of word senses using an information content based measure described by Resnik (1995).     1.01
WordNet::Similarity::vector Perl module for computing semantic relatedness of word senses using second order co-occurrence vectors of glosses of the word senses.     1.03
WordNet::Similarity::vector_pairs module for computing semantic relatedness of word senses using second order co-occurrence vectors of glosses of the word senses.     1.04
WordNet::Similarity::wup Perl module for computing semantic relatedness of word senses using the edge counting method of the of Wu & Palmer (1994)     1.01
get_wn_info Provides access to glosses related to a concept in WordNet     1.03
stem Module that find the stem of a word or the stems of a string of words, using WordNet.     1.03
vectorFile Provides access to the word vectors database.     1.03

Documentation

BNCFreq.pl  
brownFreq.pl  
compounds.pl extract compound words (collocations) from WordNet  
config.pod listing of configuration options  
developers.pod information for potential developers of measures  
install.pod how to install WordNet::Similarity  
intro.pod introduction to WordNet::Similarity  
rankFormat.pl Program to rank the output of similarity.pl.  
rawtextFreq.pl Perl program for finding the frequencies of words in raw text files  
semCorFreq.pl  
semCorRawFreq.pl  
similarity.cgi a CGI script implementing a portion of a web interface for WordNet::Similarity  
similarity.pl command line interface to WordNet::Similarity  
similarity_server.pl The server for similarity.cgi  
treebankFreq.pl Perl program for finding the frequencies of words in the Treebank corpus  
utils.pod WordNet::Similarity supporting utilities  
wnDepths.pl find depths of WordNet taxonomies  
wordVectors.pl write word vectors from WordNet glosses to a file.  
wps.cgi  

Other Files

samples/README
web/README
web/docs/explanations.html
web/docs/index.html
web/docs/instructions.html
web/docs/measures.html
web/docs/rootnode.html
web/index.html