- TYPICAL USAGE EXAMPLES
- CONFIGURATION FILE
- SEE ALSO
- COPYRIGHT AND LICENSE
WordNet::Similarity::wup - Perl module for computing semantic relatedness of word senses using the edge counting method of the of Wu & Palmer (1994)
use WordNet::Similarity::wup; use WordNet::QueryData; my $wn = WordNet::QueryData->new(); my $wup = WordNet::Similarity::wup->new($wn); my $value = $wup->getRelatedness('dog#n#1', 'cat#n#1'); my ($error, $errorString) = $wup->getError(); die $errorString if $error; print "dog (sense 1) <-> cat (sense 1) = $value\n";
Resnik (1999) revises the Wu & Palmer (1994) method of measuring semantic relatedness. Resnik uses use an edge distance method by taking into account the most specific node subsuming the two concepts. Here we have implemented the original Wu & Palmer method, which uses node-counting.
This module defines the following methods:
- $wup->getRelatedness ($synset1, $synset2)
Computes the relatedness of two word senses using a node counting scheme. For details on how relatedness is computed, see the discussion section below.
Parameters: two word senses in "word#pos#sense" format.
Returns: Unless a problem occurs, the return value is the relatedness score. If no path exists between the two word senses, then a large negative number is returned. If an error occurs, then the error level is set to non-zero and an error string is created (see the description of getError()). Note: the error level will also be set to 1 and an error string will be created if no path exists between the words.
The Wu & Palmer measure calculates relatedness by considering the depths of the two synsets in the WordNet taxonomies, along with the depth of the LCS. The formula is score = 2*depth(lcs) / (depth(s1) + depth(s2)). This means that 0 < score <= 1. The score can never be zero because the depth of the LCS is never zero (the depth of the root of a taxonomy is one). The score is one if the two input synsets are the same.
The semantic relatedness modules in this distribution are built as classes that define the following methods:
new() getRelatedness() getError() getTraceString()
See the WordNet::Similarity(3) documentation for details of these methods.
use WordNet::Similarity::wup; my $measure->new($wn, 'wup.conf');
'$wn' contains a WordNet::QueryData object that should have been constructed already. The second (and optional) parameter to the 'new' method is the path of a configuration file for the Wu-Palmer measure. If the 'new' method is unable to construct the object, then '$measure' will be undefined. This may be tested.
my ($error, $errorString) = $measure->getError (); die $errorString."\n" if $err;
To find the sematic relatedness of the first sense of the noun 'car' and the second sense of the noun 'bus' using the measure, we would write the following piece of code:
$relatedness = $measure->getRelatedness('car#n#1', 'bus#n#2');
To get traces for the above computation:
However, traces must be enabled using configuration files. By default traces are turned off.
The behavior of the measures of semantic relatedness can be controlled by using configuration files. These configuration files specify how certain parameters are initialized with the object. A configuration file may be specified as a parameter during the creation of an object using the new method. The configuration files must follow a fixed format.
Every configuration file starts with the name of the module ON THE FIRST LINE of the file. For example, a configuration file for the wup module will have on the first line 'WordNet::Similarity::wup'. This is followed by the various parameters, each on a new line and having the form 'name::value'. The 'value' of a parameter is option (in the case of boolean parameters). In case 'value' is omitted, we would have just 'name::' on that line. Comments are allowed in the configuration file. Anything following a '#' is ignored till the end of the line.
The module parses the configuration file and recognizes the following parameters:
The value of this parameter specifies the level of tracing that should be employed for generating the traces. This value is an integer equal to 0, 1, or 2. If the value is omitted, then the default value, 0, is used. A value of 0 switches tracing off. A value of 1 or 2 switches tracing on. A trace of level 1 means the synsets are represented as word#pos#sense strings, while for level 2, the synsets are represented as word#pos#offset strings.
The value of this parameter specifies whether or not caching of the relatedness values should be performed. This value is an integer equal to 0 or 1. If the value is omitted, then the default value, 1, is used. A value of 0 switches caching 'off', and a value of 1 switches caching 'on'.
The value of this parameter indicates the size of the cache, used for storing the computed relatedness value. The specified value must be a non-negative integer. If the value is omitted, then the default value, 5,000, is used. Setting maxCacheSize to zero has the same effect as setting cache to zero, but setting cache to zero is likely to be more efficient. Caching and tracing at the same time can result in excessive memory usage because the trace strings are also cached. If you intend to perform a large number of relatedness queries, then you might want to turn tracing off.
The value of this parameter indicates whether or not a unique root node should be used. In WordNet, there is no unique root node for the noun and verb taxonomies. If this parameter is set to 1 (or if the value is omitted), then certain measures (wup, path, lch, res, lin, and jcn) will "fake" a unique root node. If the value is set to 0, then no unique root node will be used. If the value is omitted, then the default value, 1, is used.
The value for this parameter should be a string that specifies the location of a synset depths file (as generated by wnDepths.pl. If no path is specified, then the default file is used, which was generated when the Similarity package was installed.
perl(1), WordNet::Similarity(3), WordNet::QueryData(3)
Ted Pedersen, University of Minnesota Duluth tpederse at d.umn.edu Jason Michelizzi, University of Minnesota Duluth mich0212 at d.umn.edu Siddharth Patwardhan, University of Utah, Salt Lake City sidd at cs.utah.edu
Copyright (c) 2005, Ted Pedersen, Jason Michelizzi and Siddharth Patwardhan
This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
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The Free Software Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
Note: a copy of the GNU General Public License is available on the web at <http://www.gnu.org/licenses/gpl.txt> and is included in this distribution as GPL.txt.