Documentation

Revision history for WordNet::Similarity
[documentation] Description of all configuration options for measures
[documentation] Instructions on how to write a new measure for WordNet::Similarity
[documentation] How to install WordNet::Similarity
[documentation] Introduction to WordNet::Similarity
[documentation] Overview of WordNet::Similarity measure modules
Todo list for WordNet::Similarity
[documentation] WordNet::Similarity supporting utilities
Compute Information Content based on British National Corpus (World Edition)
Compute Information Content from the Brown Corpus
extract compound words (collocations) from WordNet
Measure the correlation between two different rankings of word pairs measured for semantic relatedness.
Compute Information Content from Raw / Plain Text
Compute Information Content from SemCor sense-tagged corpus
Compute Information Content from SemCor corpus (raw form, without using sense-tags)
Command line interface to WordNet::Similarity
[Web] The backend WordNet::Similarity server for the Web Interface
Compute Information Content from Penn Treebank 2
Find the depths of WordNet taxonomies
Write word vectors from WordNet glosses to a file for use by vector and vector_pairs measures

Modules

Perl modules for computing measures of semantic relatedness.
methods to find the depth of synsets in WordNet taxonomies
Support functions for frequency counting programs used to estimate the information content of concepts.
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)
Some tools for use with WordNet.
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 (used by the vector and vector_pairs WordNet::Similarity measures).