File Coverage

blib/lib/WordNet/Similarity/res.pm

Criterion	Covered	Total	%
statement	4	6	66.6
branch			n/a
condition			n/a
subroutine	2	2	100.0
pod			n/a
total	6	8	75.0

# WordNet::Similarity::res.pm version 2.04
# (Last updated $Id: res.pm,v 1.21 2008/03/27 06:21:17 sidz1979 Exp $)
#
# Semantic Similarity Measure package implementing the measure
# described by Resnik (1995).
#
# Copyright (c) 2005,
#
# 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, Univeristy of Minnesota Duluth
# mich0212 at d.umn.edu
#
# 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.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to
#
# The Free Software Foundation, Inc.,
# 59 Temple Place - Suite 330,
# Boston, MA  02111-1307, USA.
#
# ------------------------------------------------------------------

package WordNet::Similarity::res;

=head1 NAME

WordNet::Similarity::res - Perl module for computing semantic relatedness
of word senses using an information content based measure described by
Resnik (1995).

=head1 SYNOPSIS

  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";

=head1 DESCRIPTION

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:

=over

=cut

use strict;
use WordNet::Similarity::ICFinder;

our @ISA = qw/WordNet::Similarity::ICFinder/;

our $VERSION = '2.04';

# The 'new' method for this class is supplied by WordNet::Similarity

=item $res->getRelatedness ($synset1, $synset2)

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.

=cut

sub getRelatedness
{
  my $self = shift;
  my $wps1 = shift;
  my $wps2 = shift;
  my $wn = $self->{wn};

  my $class = ref $self || $self;
  # Check the existence of the WordNet::QueryData object.
  unless ($wn) {
    $self->{errorString} .= "\nError (${class}::getRelatedness()) - ";
    $self->{errorString} .= "A WordNet::QueryData object is required.";
    $self->{error} = 2;
    return undef;
  }

  # JM 1-21-04
  # moved input validation code to parseWps() in a super-class
  my $ret = $self->parseWps ($wps1, $wps2);
  ref $ret or return $ret;
  my ($word1, $pos1, undef, $offset1, $word2, $pos2, undef, $offset2) = @{$ret};

  # Initialize traces.
  $self->{traceString} = "";

  my $pos = $pos1;

  # Now check if the similarity value for these two synsets is in
  # fact in the cache... if so return the cached value.
  my $relatedness =
    $self->{doCache} ? $self->fetchFromCache ($wps1, $wps2) : undef;
  defined $relatedness and return $relatedness;

  # Now get down to really finding the relatedness of these two.
  $self->{traceString} = "";

  unless ($offset1 and $offset2) {
    $self->{errorString} .= "\nWarning (${class}::getRelatedness()) - ";
    $self->{errorString} .= "Input senses not found in WordNet.";
    $self->{error} = ($self->{'error'} < 1) ? 1 : $self->{'error'};
    return undef;
  }

  my @LCSs = $self->getLCSbyIC ($offset1, $offset2, $pos1, "offset");

  my $ref = shift @LCSs;

  unless (defined $ref) {
    return $self->UNRELATED;
  }

  my ($lcs, $ic) = @{$ref};

  my $score = $ic;

  $self->{doCache} and $self->storeToCache ($wps1, $wps2, $score);
  return $score;
}

# JM 1-16-04
# moved subroutine _getLeastCommonSubsumers to ICFinder.pm

1;

__END__