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Documentation

listing of configuration options
information for potential developers of measures
how to install WordNet::Similarity
introduction to WordNet::Similarity
modules for computing semantic relatedness.
WordNet::Similarity supporting utilities
extract compound words (collocations) from WordNet
Program to rank the output of similarity.pl.
Perl program for finding the frequencies of words in raw text files
command line interface to WordNet::Similarity
Perl program for finding the frequencies of words in the Treebank corpus
find depths of WordNet taxonomies
write word vectors from WordNet glosses to a file.
The server for similarity.cgi

Modules

Perl modules for computing measures of semantic relatedness.
methods to find the depth of synsets in WordNet taxonomies
module to implement gloss finding methods for WordNet::Similarity measures of semantic relatedness (specifically, lesk and vector)
a module for finding the information content of concepts in WordNet
module to implement path finding methods (by node counting) for WordNet::Similarity measures of semantic relatedness
Perl module for computing semantic relatedness of word senses using the method described by Hirst and St-Onge (1998).
Perl module for computing semantic relatedness of word senses according to the method described by Jiang and Conrath (1997).
Perl module for computing semantic relatedness of word senses using the method described by Leacock and Chodorow (1998).
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.
Perl module for computing semantic relatedness of word senses using the information content based measure described by Lin (1998).
Perl module for computing semantic relatedness of word senses by counting nodes in the noun and verb WordNet 'is-a' hierarchies.
Perl module for computing semantic relatedness of word senses using a random measure.
Perl module for computing semantic relatedness of word senses using an information content based measure described by Resnik (1995).
Perl module for computing semantic relatedness of word senses using second order co-occurrence vectors of glosses of the word senses.
module for computing semantic relatedness of word senses using second order co-occurrence vectors of glosses of the word senses.
Perl module for computing semantic relatedness of word senses using the edge counting method of the of Wu & Palmer (1994)
Provides access to glosses related to a concept in WordNet
Module that find the stem of a word or the stems of a string of words, using WordNet.
Provides access to the word vectors database.