2003-10-28 16:16:42 +01:00
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This package consists of Perl modules along with supporting Perl programs
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that implement the semantic relatedness measures described by Leacock
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Chodorow (1998), Jiang Conrath (1997), Resnik (1995), Lin (1998), Hirst St
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Onge (1998), Wu Palmer (1994), the adapted gloss overlap measure by
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Banerjee and Pedersen (2002), and a measure based on context vectors
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by Patwardhan (2003). The details of the Vector measure are described in the
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Master's thesis work done by Patwardhan (2003) at the University of Minnesota
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Duluth. The Perl modules are designed as objects with methods that take as
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input two word senses. The semantic relatedness of these word senses is
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returned by these methods. A quantitative measure of the degree to which two
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word senses are related has wide ranging applications in numerous areas, such
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as word sense disambiguation, information retrieval, etc. For example, in
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order to determine which sense of a given word is being used in a particular
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context, the sense having the highest relatedness with its context word
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senses is most likely to be the sense being used. Similarly, in information
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retrieval, retrieving documents containing highly related concepts are more
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likely to have higher precision and recall values.
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Add p5-WordNet-Similarity.
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)
and the adapted gloss overlap measure by Banerjee and Pedersen (2002). The Perl
modules are designed as object classes 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.
2003-07-08 03:16:27 +02:00
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A command line interface to these modules is also present in the package. The
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simple, user-friendly interface returns the relatedness measure of two given
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2003-10-28 16:16:42 +01:00
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words.
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Add p5-WordNet-Similarity.
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)
and the adapted gloss overlap measure by Banerjee and Pedersen (2002). The Perl
modules are designed as object classes 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.
2003-07-08 03:16:27 +02:00
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WWW: http://search.cpan.org/dist/WordNet-Similarity/
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