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.\"
.IX Title "WagnerFischer 3pm"
.TH WagnerFischer 3pm "2021-01-01" "perl v5.32.0" "User Contributed Perl Documentation"
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.SH "NAME"
Text::WagnerFischer \- An implementation of the Wagner\-Fischer edit distance
.SH "SYNOPSIS"
.IX Header "SYNOPSIS"
.Vb 1
\& use Text::WagnerFischer qw(distance);
\&
\& print distance("foo","four");# prints "2"
\&
\& print distance([0,1,2],"foo","four");# prints "3"
\&
\&
\& my @words=("four","foo","bar");
\&
\& my @distances=distance("foo",@words); 
\& print "@distances"; # prints "2 0 3"
\&
\& @distances=distance([0,2,1],"foo",@words); 
\& print "@distances"; # prints "3 0 3"
.Ve
.SH "DESCRIPTION"
.IX Header "DESCRIPTION"
This module implements the Wagner-Fischer dynamic programming technique,
used here to calculate the edit distance of two strings.
The edit distance is a measure of the degree of proximity between two strings,
based on \*(L"edits\*(R": the operations of substitutions, deletions or insertions
needed to transform the string into the other one (and vice versa).
A cost (weight) is needed for every of the operation defined above:
.PP
.Vb 3
\&            / a if x=y (cost for letter match)
\& w(x,y) =  |  b if x=\- or y=\- (cost for insertion/deletion operation)
\&            \e c if x!=y (cost for letter mismatch)
.Ve
.PP
These costs are given through an array reference as first argument of the 
distance subroutine: [a,b,c].
If the costs are not given, a default array cost is used: [0,1,1] that is the
case of the Levenshtein edit distance:
.PP
.Vb 3
\&            / 0 if x=y (cost for letter match)
\& w(x,y) =  |  1 if x=\- or y=\- (cost for insertion/deletion operation)
\&            \e 1 if x!=y (cost for letter mismatch)
.Ve
.PP
This particular distance is the exact number of edit needed to transform 
the string into the other one (and vice versa).
When two strings have distance 0, they are the same.
Note that the distance is calculated to reach the _minimum_ cost, i.e.
choosing the most economic operation for each edit.
.SH "EXTENDING (by Daniel Yacob)"
.IX Header "EXTENDING (by Daniel Yacob)"
New modules may build upon Text::WagnerFischer as a base class.
This is practical when you would like to apply the algorithm
to non-Roman character sets or would like to change some part
of the algorithm but not another.
.PP
The following example demonstrates how to use the WagnerFisher
distance algorithm but apply your own weight function in a new
package:
.PP
.Vb 2
\&  package Text::WagnerFischer::MyModule;
\&  use base qw( Text::WagnerFischer );
\&
\&  #
\&  # Link to the WagnerFisher "distance" function so that the
\&  # new module may also export it:
\&  #
\&  use vars qw(@EXPORT_OK);
\&
\&  @EXPORT_OK = qw(&distance);
\&
\&  *distance = \e&Text::WagnerFischer::distance;
\&
\&  #
\&  # "override" the _weight function with the a one:
\&  #
\&  *Text::WagnerFischer::_weight = \e&_my_weight;
\&
\&  #
\&  # "override" the default WagnerFischer "costs" table:
\&  #
\&  $Text::WagnerFischer::REFC = [0,2,3,1,1];
\&
\&  sub _my_weight {
\&    :
\&    :
\&    :
\&  }
.Ve
.SH "AUTHOR"
.IX Header "AUTHOR"
Copyright 2002,2003 Dree Mistrut <\fIdree@friul.it\fR>
.PP
This package is free software and is provided \*(L"as is\*(R" without express
or implied warranty. You can redistribute it and/or modify it under 
the same terms as Perl itself.
.SH "SEE ALSO"
.IX Header "SEE ALSO"
\&\f(CW\*(C`Text::Levenshtein\*(C'\fR, \f(CW\*(C`Text::PhraseDistance\*(C'\fR