NAME

Semantic::Similarity::vector - Perl module for computing semantic relatedness of concepts using second order co-occurrence vectors of definitions of the concepts.

SYNOPSIS

use Semantic::Similarity::vector;

use WordNet::QueryData;

my $interface = WordNet::QueryData->new();

my $vector = Semantic::Similarity::vector->new($interface);

my $value = $vector->getRelatedness("car#n#1", "bus#n#2");

($error, $errorString) = $vector->getError();

die "$errorString\n" if($error);

print "car (sense 1) <-> bus (sense 2) = $value\n";

DESCRIPTION

Schütze (1998) creates what he calls context vectors (second order co-occurrence vectors) of pieces of text for the purpose of Word Sense Discrimination. This idea is adopted by Patwardhan and Pedersen to represent the concepts by second-order co-occurrence vectors of their dictionary definitions. The relatedness of two concepts is then computed as the cosine of their representative vectors.

USAGE

The semantic relatedness modules in this distribution are built as classes that expose the following methods: new() getRelatedness() getError() getTraceString()

See the Semantic::Similarity(3) documentation for details of these methods.

TYPICAL USAGE EXAMPLES

To create an object of the vector measure, we would have the following lines of code in the perl program.

use Semantic::Similarity::vector;
$measure = Semantic::Similarity::vector->new($interface, '/home/sid/vector.conf');

The reference of the initialized object is stored in the scalar variable '$measure'. '$interface' contains a interface object that should have been created earlier in the program. The interface object provides the interface to the backend taxonomy (For example, WordNet, Snomed, ,UMLS, etc.). The second parameter to the 'new' method is the path of the configuration file for the vector 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 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:

print $measure->getTraceString();

However, traces must be enabled using configuration files. By default traces are turned off.

CONFIGURATION FILE

The behaviour 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 specififed 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 the name of the module ON THE FIRST LINE of the file. For example, a configuration file for the vector module will have on the first line 'Semantic::Similarity::vector'. 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:

(a) 'trace::' -- The value of this parameter specifies the level of tracing that should be employed for generating the traces. This value is an integer 0, 1 or 2. A value of 0 switches tracing off. A value of 1 displays as traces only the gloss overlaps found. A value of 2 displays as traces, all the text being compared.

(b) 'vectordb::' -- Value is a Berkeley DB database file containing word vectors, i.e. co-occurrence vectors for all the words in the definitions.

(c) 'stop::' -- The value is a string that specifies the path of a file containing a list of stop words that should be ignored in the vectors.

(d) 'compounds::' -- The value is a string that specifies the path of a file containing a list of compound words in the taxonomy.

(e) 'stem::' -- can take values 0 or 1 or the value can be omitted, in which case it takes the value 1, i.e. switches 'on' stemming. A value of 0 switches stemming 'off'. When stemming is enabled, all the words of the definitions are stemmed before their vectors are created.

(f) 'cache::' -- can take values 0 or 1 or the value can be omitted, in which case it takes the value 1, i.e. switches 'on' caching. A value of 0 switches caching 'off'. By default caching is enabled.

SEE ALSO

perl(1), Semantic::Similarity(3)

http://www.cogsci.princeton.edu/~wn

http://www.ai.mit.edu/people/jrennie/WordNet

http://groups.yahoo.com/group/wn-similarity

AUTHORS

Siddharth Patwardhan <sidd@cs.utah.edu>
Serguei Pakhomov <pakhomov.serguei@mayo.edu>
Ted Pedersen <tpederse@d.umn.edu>

COPYRIGHT AND LICENSE

Copyright 2004 by Siddharth Patwardhan, Serguei Pakhomov and Ted Pedersen

This library is free software; you can redistribute it and/or modify it under the same terms as Perl itself.

cpanm UMLS::Similarity

perl -MCPAN -e shell
install UMLS::Similarity