# run perldoc on this file to get nicely formatted documentation

=head1 NAME

intro.pod - introduction to WordNet::Similarity

=head1 CONTENTS

I<intro.pod>, I<install.pod>, I<utils.pod>, I<modules.pod>, I<developers.pod>,
I<config.pod>, L<FDL.txt>

=head1 SYNOPSIS

You can use pod2html, pod2latex, pod2man, or pod2text to get this
documentation in a different format.  See the man pages for pod2html, etc.
These translators should come with Perl, but you can also download them
from L<http://search.cpan.org>.

=head1 DESCRIPTION

This package consists of Perl modules along with supporting Perl programs
that implement the semantic relatedness measures described by Leacock &
Chodorow (1998), Jiang & Conrath (1997), Resnik (1995), Lin (1998), Hirst &
St-Onge (1998), Wu & Palmer (1994), the adapted gloss overlap measure by 
Banerjee and Pedersen (2002), and two measures based on context vectors
by Patwardhan (2003). The details of the vector measure are described in  
the Master's thesis work of Patwardhan (2003) at the University of  
Minnesota Duluth, and the vector_pairs measure is derived from that. 

The Perl modules are designed as objects with methods that take as
input two word senses. The semantic relatedness of these word senses is
returned by these methods. A quantitative measure of the degree to which two
word senses are related has wide ranging applications in numerous areas, such
as word sense disambiguation, information retrieval, etc. For example, in
order to determine which sense of a given word is being used in a particular
context, the sense having the highest relatedness with its context word
senses is most likely to be the sense being used. Similarly, in information
retrieval, retrieving documents containing highly related concepts are more
likely to have higher precision and recall values.

A command line interface to these modules is also present in the
package. The simple, user-friendly interface returns the relatedness
measure of two given words. A number of switches and options have been
provided to modify the output and enhance it with trace information and
other useful output. Details of the usage are provided in other sections of
this README. Supporting utilities for generating information content files
from various corpora are also available in the package. The information
content files are required by three of the measures for computing the
relatedness of concepts.

Discussion about the package and online help for the package is available
on the wn-similarity mailing list. To join the list, go to 

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

The following sections describe the organization of this software package
and how to use it. A few typical examples are given to help clearly
understand the usage of the modules and the supporting utilities.

=head1 SEMANTIC RELATEDNESS

We observe that humans find it extremely easy to say if two words are
related and if one word is more related to a given word than another. For
example, if we come across two words -- 'car' and 'bicycle', we know they
are related as both are means of transport. Also, we easily observe that
'bicycle' is more related to 'car' than 'fork' is. But is there some way to
assign a quantitative value to this relatedness? Some ideas have been put
forth by researchers to quantify the concept of relatedness of words, with
encouraging results.

A number of different measures of relatedness have been implemented in
this software package. These include a simple edge counting approach and
a random method for measuring relatedness. The measures rely heavily on the
vast store of knowledge available in the online electronic dictionary --
WordNet. So, we use a Perl interface for WordNet called WordNet::QueryData
to make it easier for us to access WordNet. The modules in this package
REQUIRE that the WordNet::QueryData module be installed on the system
before these modules are installed.

=head1 CONTENTS

The package contains the semantic relatedness modules, some support Perl
utilities and some sample configuration files, data files and programs.

=head2 Modules

All the modules that will be installed in the Perl system directory are
present in the '/lib' directory tree of the package. These include the
semantic relatedness modules -- jcn.pm, res.pm, lin.pm, lch.pm, hso.pm,
lesk.pm, vector.pm, vector_pairs.pm, wup.pm, path.pm and random.pm --  
present in the /lib/WordNet/Similarity subdirectory and the supporting 
modules get_wn_info.pm and string_compare.pm. There also exists a 
WordNet/Similarity.pm module that currently serves as a base class for all
the relatedness modules and contains Perl documentation. All these modules,
once installed in the Perl system directory, can be directly used by Perl
programs.

=head2 Supporting Utilities

The '/utils' subdirectory of the package contains supporting Perl
programs. 'similarity.pl' is a command-line interface to the relatedness
modules. A number of Perl programs, that generate information content files
from various corpora, are provided. As part of the standard install, these
are also installed into the system directories, and can be accessed from
any working directory if the common system directories (/usr/bin,
/usr/local/bin, etc) are in your path.

=head2 Samples

If you downloaded this package as a tar-gzipped file from the web, you will
find a '/samples' subdirectory in the package.  There is a separate README
in that directory.  The directory contains sample configuration files for the
modules, sample programs showing usage of the modules and sample data files
(e.g., relation files).

=head1 SOFTWARE COPYRIGHT AND LICENSE

Copyright (c) 2005, Ted Pedersen, Siddharth Patwardhan, Satanjeev Banerjee, 
and Jason Michelizzi

This suite of programs 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.

Note: The text of the GNU General Public License is provided in the file
'GPL.txt' that you should have received with this distribution.

=head1 ACKNOWLEDGEMENTS

We would like to thank the following for their support and contribution
towards the development of this package. We thank Jason Rennie for his
QueryData package, the WordNet guys at Princeton for WordNet, Resnik,
Hirst, St-Onge, Jiang, Conrath, Lin, Wu, Palmer, Leacock, and Chodorow
for their algorithms and work on the relatedness measures. We also thank
Bano (Satanjeev Banerjee) for his work on the adapted gloss overlap module.
We are grateful to Wybo Wiersma for contributing his optimizations to the
GlossFinder code.

=head1 REFERENCES

=over

=item 1

Wu Z. and Palmer M. 1994. Verb Semantics and Lexical Selection. In
Proceedings of the 32nd Annual Meeting of the Association for
Computational Linguistics.  Las Cruces, New Mexico.

=item 2

Resnik P. 1995. Using information content to evaluate semantic
similarity. In Proceedings of the 14th International Joint Conference
on Artificial Intelligence, pages 448-453, Montreal.

=item 3

Jiang J. and Conrath D. 1997. Semantic similarity based on corpus
statistics and lexical taxonomy. In Proceedings of International
Conference on Research in Computational Linguistics, Taiwan.

=item 4

Fellbaum C., editor. WordNet: An electronic lexical database. MIT Press, 
1998.

=item 5

Leacock C. and Chodorow M. 1998. Combining local context and WordNet
similarity for word sense identification. In Fellbaum 1998,
pp. 265-283.

=item 6

Lin D. 1998. An information-theoretic definition of similarity. In
Proceedings of the 15th International Conference on Machine Learning,
Madison, WI.

=item 7

Hirst G. and St-Onge D. 1998. Lexical Chains as representations of
context for the detection and correction of malapropisms. In Fellbaum
1998, pp. 305-332.

=item 8

SchE<uuml>tze H. 1998. Automatic Word Sense Discrimination. Computational
Linguistics, 24(1):97-123.

=item 9

Resnik P. 1999. Semantic Similarity in a Taxonomy: An Information-
Based Measure and its Applications to Problems of Ambiguity in
Natural Language. Journal of Artificial Intelligence Research, 11,
95-130.

=item 10

Budanitsky A. and Hirst G. 2001. Semantic distance in WordNet: An
experimental, application-oriented evaluation of five measures. In
Workshop on WordNet and Other Lexical Resources, Second meeting of the
North American Chapter of the Association for Computational
Linguistics. Pittsburgh, PA.

=item 11

Banerjee S. and Pedersen T. 2002. An Adapted Lesk Algorithm for Word
Sense Disambiguation Using WordNet. In Proceeding of the Fourth
International Conference on Computational Linguistics and Intelligent
Text Processing (CICLING-02). Mexico City.

=item 12

Patwardhan S., Banerjee S. and Pedersen T. 2002. Using Semantic
Relatedness for Word Sense Disambiguation. In Proceedings of the
Fourth International Conference on Intelligent Text Processing and
Computational Linguistics, Mexico City.

=item 13

Banerjee S. Adapting the Lesk algorithm for word sense
disambiguation to WordNet. Master Thesis, University of Minnesota,
Duluth, 2002.

=item 14

Patwardhan S. Incorporating dictionary and corpus information into a
vector measure of semantic relatedness. Master Thesis, University of
Minnesota, Duluth, 2003.

=back

=head1 SEE ALSO

L<http://groups.yahoo.com/group/wn-similarity>,
L<http://search.cpan.org/dist/WordNet-Similarity>,
L<http://wn-similarity.sourceforge.net>

=head1 AUTHORS

 Ted Pedersen, University of Minnesota Duluth
 tpederse at d.umn.edu

 Siddharth Patwardhan, University of Utah, Salt Lake City
 sidd at cs.utah.edu

 Satanjeev Banerjee, Carnegie Mellon University, Pittsburgh
 banerjee+ at cs.cmu.edu

 Jason Michelizzi, University of Minnesota Duluth
 mich0212 at d.umn.edu

=head1 DOCUMENTATION COPYRIGHT AND LICENSE

Copyright (c) 2005, Ted Pedersen, Siddharth Patwardhan, Satanjeev Banerjee, 
and Jason Michelizzi

Permission is granted to copy, distribute and/or modify this document
under the terms of the GNU Free Documentation License, Version 1.2
or any later version published by the Free Software Foundation;
with no Invariant Sections, no Front-Cover Texts, and no Back-Cover
Texts.

Note: a copy of the GNU Free Documentation License is available on
the web at L<http://www.gnu.org/copyleft/fdl.html> and is included in
this distribution as FDL.txt.

=cut
