WordNet::Similarity::res - Perl module for computing semantic relatedness of word senses using an information content based measure described by Resnik (1995).
use WordNet::Similarity::res; use WordNet::QueryData; my $wn = WordNet::QueryData->new(); my $object = WordNet::Similarity::res->new($wn); my $value = $object->getRelatedness("car#n#1", "bus#n#2"); ($error, $errorString) = $object->getError(); die "$errorString\n" if($error); print "car (sense 1) <-> bus (sense 2) = $value\n";
Resnik (1995) uses the information content of concepts, computed from their frequency of occurrence in a large corpus, to determine the semantic relatedness of word senses. This module implements this measure of semantic relatedness.
The following methods are defined:
Computes the relatedness of two word senses using an information content scheme. The relatedness is equal to the information content of the least common subsumer of the input synsets.
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 value returned by the res measure is equal to the information content of the Least Common Subsumer (LCS) of the two input synsets. This means that the value will be greater-than or equal-to zero. The upper bound on the value is generally quite large and varies depending upon the information content file being used. To be precise, the upper bound is ln (N), where N is the sum of the frequencies of all the synsets in the information content files.
The Resnick measure is sometimes considered a "coarse" measure. Since the relatedness of two synsets depends only upon the information content of their LCS, all pairs of synsets that have the same LCS will have exactly the same relatedness. For example, the pairs dog#n#1-monkey#n#1 and canine#n#1-primate#n#2.
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 res measure, we would have the following lines of code in the Perl program.
use WordNet::Similarity::res; $measure = WordNet::Similarity::res->new($wn, '/home/sid/res.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 res 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 res module will have on the first line 'WordNet::Similarity::res'. 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 path of an information content file containing the frequency of occurrence of every WordNet concept in a large corpus. A number of utility programs are included in this distribution that can be used to generate an infocontent file (see utils.pod). If no path is specified, then the default infocontent file is used, which was generated from SemCor using the sense-tags.
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
Copyright (c) 2005, Ted Pedersen, Siddharth Patwardhan and Jason Michelizzi
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