Text::Fingerprint - perform simple text clustering by key collision
#!/usr/bin/env perl use common::sense; use Text::Fingerprint qw(:all); my $str = q( À noite, vovô Kowalsky vê o ímã cair no pé do pingüim queixoso e vovó põe açúcar no chá de tâmaras do jabuti feliz. ); say fingerprint($str); # a acucar cair cha de do e feliz ima jabuti kowalsky # no noite o pe pinguim poe queixoso tamaras ve vovo say fingerprint_ngram($str); # abacadaialamanarasbucachcudedoeaedeieleoetevfeg # uhaifiminiritixizjakokylilsmamqngnoocoeoiojokop # osovowpepipoqurarnsdsksotatetiucueuiutvevowaxoyv say fingerprint_ngram($str, 1); # abcdefghijklmnopqrstuvwxyz
Text clustering functions borrowed from the Google Refine. Can be useful for finding groups of different values that might be alternative representations of the same thing. For example, the two strings "New York" and "new york" are very likely to refer to the same concept and just have capitalization differences. Likewise, "Gödel" and "Godel" probably refer to the same person.
The process that generates the key from a
$string value is the following (note that the order of these operations is significant):
The n-gram fingerprint method is similar to the
fingerprint method described above but instead of using whitespace separated tokens, it uses n-grams, where the
$n (or the size in chars of the token) can be specified by the user (default: 2). Algorithm steps:
Fingerprint functions are not exactly the same as those found in Google Refine! They were slightly changed to take advantage of the superb Perl handling of Unicode characters.
Stanislaw Pusep <email@example.com>
This software is copyright (c) 2014 by Stanislaw Pusep.
This is free software; you can redistribute it and/or modify it under the same terms as the Perl 5 programming language system itself.