WordNet::Similarity::lch - Perl module for computing semantic relatedness of word senses using the method described by Leacock and Chodorow (1998).
use WordNet::Similarity::lch; use WordNet::QueryData; my $wn = WordNet::QueryData->new(); my $myobj = WordNet::Similarity::lch->new($wn); my $value = $myobj->getRelatedness("car#n#1", "bus#n#2"); ($error, $errorString) = $myobj->getError(); die "$errorString\n" if($error); print "car (sense 1) <-> bus (sense 2) = $value\n";
This module computes the semantic relatedness of word senses according to a method described by Leacock and Chodorow (1998). This method counts up the number of edges between the senses in the 'is-a' hierarchy of WordNet. The value is then scaled by the maximum depth of the WordNet 'is-a' hierarchy. A relatedness value is obtained by taking the negative log of this scaled value.
This method is internally called to determine the parts of speech this measure is capable of dealing with.
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 relatedness measure proposed by Leacock and Chodorow is -log (length / (2 * D)), where length is the length of the shortest path between the two synsets (using node-counting) and D is the maximum depth of the taxonomy.
The fact that the lch measure takes into account the depth of the taxonomy in which the synsets are found means that the behavior of the measure is profoundly affected by the presence or absence of a unique root node. If there is a unique root node, then there are only two taxonomies: one for nouns and one for verbs. All nouns, then, will be in the same taxonomy and all verbs will be in the same taxonomy. D for the noun taxonomy will be somewhere around 18, depending upon the version of WordNet, and for verbs, it will be 14. If the root node is not being used, however, then there are nine different noun taxonomies and over 560 different verb taxonomies, each with a different value for D.
If the root node is not being used, then it is possible for synsets to belong to more than one taxonomy. For example, the synset containing turtledove#n#2 belongs to two taxonomies: one rooted at group#n#1 and one rooted at entity#n#1. In such a case, the relatedness is computed by finding the LCS that results in the shortest path between the synsets. The value of D, then, is the maximum depth of the taxonomy in which the LCS is found. If the LCS belongs to more than one taxonomy, then the taxonomy with the greatest maximum depth is selected (i.e., the largest value for D).
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.
To create an object of the lch measure, we would have the following lines of code in the Perl program.
use WordNet::Similarity::lch; $measure = WordNet::Similarity::lch->new($wn, '/home/sid/lch.conf');
The reference of the initialized object is stored in the scalar variable '$measure'. '$wn' contains a WordNet::QueryData object that should have been created earlier in the program. The second parameter to the 'new' method is the path of the configuration file for the lch measure. If the 'new' method is unable to create the object, '$measure' would be undefined. This, as well as any other error/warning may be tested.
die "Unable to create object.\n" if(!defined $measure); ($err, $errString) = $measure->getError(); die $errString."\n" if($err);
To find the semantic 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 within 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 WordNet::Similarity::lch module will have on the first line 'WordNet::Similarity::lch'. This is followed by the various parameters, each on a new line and having the form 'name::value'. The 'value' of a parameter is optional (in case of boolean parameters). In case 'value' is omitted, we would have just 'name::' on that line. Comments are supported 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 level of 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 taxonomy 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.
Ted Pedersen, University of Minnesota Duluth tpederse at d.umn.edu Siddharth Patwardhan, University of Utah, Salt Lake City sidd at cs.utah.edu Jason Michelizzi, University of Minnesota Duluth mich0212 at d.umn.edu
To report bugs, go to http://groups.yahoo.com/group/wn-similarity/ or e-mail tpederse at d.umn.edu.
Copyright (c) 2005, Ted Pedersen, Siddharth Patwardhan and Jason Michelizzi
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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