1 | ###########################################################################
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2 | #
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3 | # textcat.pm -- Identify the language of a piece of text
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4 | #
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5 | #
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6 | # This file is based on TextCat version 1.08 by Gertjan van Noord
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7 | # Copyright (C) 1997 Gertjan van Noord ([email protected])
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8 | # TextCat is available from: http://odur.let.rug.nl/~vannoord/TextCat
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9 | #
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10 | # It was modified by Gordon Paynter ([email protected]) and turned
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11 | # into a package for use in Greenstone digital library system. Most of
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12 | # the modifications consist of commenting out or deleting functionality
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13 | # I don't need.
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14 | #
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15 | #
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16 | # This program is free software; you can redistribute it and/or modify
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17 | # it under the terms of the GNU General Public License as published by
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18 | # the Free Software Foundation; either version 2 of the License, or
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19 | # (at your option) any later version.
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20 | #
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21 | # This program is distributed in the hope that it will be useful,
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22 | # but WITHOUT ANY WARRANTY; without even the implied warranty of
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23 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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24 | # GNU General Public License for more details.
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25 | #
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26 | # You should have received a copy of the GNU General Public License
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27 | # along with this program; if not, write to the Free Software
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28 | # Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
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29 | #
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30 | ###########################################################################
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31 |
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32 | package textcat;
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33 |
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34 | use strict;
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35 |
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36 | # OPTIONS
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37 | my $model_dir = $ENV{'GSDLHOME'} . "/perllib/textcat";
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38 |
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39 | my $opt_f = 1; # Ngrams which occur <= this number of times are removed
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40 | my $opt_t = 400; # topmost number of ngrams that should be used
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41 | my $opt_u = 1.05; # how much worse result must be before it is ignored
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42 |
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43 | my $non_word_characters = '0-9\s';
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44 |
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45 | # caching related
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46 | my %filename_cache = (); # map of cached text-strings each to array of char-encodings for the strings themselves
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47 | my %filecontents_cache = (); # map of cached filenames to array of char-encodings for the contents of the files
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48 | my $MAX_CACHE_SIZE = 1000;
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49 |
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50 | sub new {
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51 | my $class = shift (@_);
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52 | my ($tmp_f, $tmp_t, $tmp_u) = @_;
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53 |
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54 | my $self = {};
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55 |
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56 | # open directory to find which languages are supported
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57 | opendir DIR, "$model_dir" or die "directory $model_dir: $!\n";
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58 | my @languages = sort(grep { s/\.lm// && -r "$model_dir/$_.lm" } readdir(DIR));
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59 | closedir DIR;
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60 | @languages or die "sorry, can't read any language models from $model_dir\n" .
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61 | "language models must reside in files with .lm ending\n";
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62 |
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63 | # load model and count for each language.
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64 | foreach my $language (@languages) {
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65 | my %ngram=();
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66 | my $rang=1;
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67 | open(LM, "$model_dir/$language.lm") || die "cannot open $language.lm: $!\n";
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68 | while (<LM>) {
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69 | chomp;
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70 | # only use lines starting with appropriate character. Others are ignored.
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71 | if (/^[^$non_word_characters]+/o) {
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72 | $self->{'ngrams'}->{$language}->{$&} = $rang++;
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73 | }
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74 | }
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75 | close(LM);
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76 | }
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77 |
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78 | $self->{'languages'} = \@languages;
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79 |
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80 | $self->{'opt_f'} = defined($tmp_f) ? $tmp_f : $opt_f;
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81 | $self->{'opt_t'} = defined($tmp_t) ? $tmp_t : $opt_t;
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82 | $self->{'opt_u'} = defined($tmp_u) ? $tmp_u : $opt_u;
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83 | $self->{'max_cache_size'} = $MAX_CACHE_SIZE;
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84 |
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85 | return bless $self, $class;
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86 | }
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87 |
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88 |
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89 | # CLASSIFICATION
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90 | #
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91 | # What language is a text string?
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92 | # Input: text string
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93 | # Output: array of language names
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94 | # $languages is the set of language models to consider (to textcat on)
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95 | # Can be set to filter out language models that don't belong to the given encoding
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96 | # in order to obtain a list of the probable languages for that known encoding.
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97 | # $filter_by_encoding indicates what encoding to narrow the search for languages down to.
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98 | # This is for when we already know the encoding, but we're still looking for the language.
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99 | sub classify {
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100 | my ($self, $inputref, $filter_by_encoding)=@_;
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101 | my $languages;
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102 | @$languages = ();
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103 |
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104 | # filter language filenames by encoding
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105 | if(defined $filter_by_encoding) {
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106 | # make sure to normalize language and filtering encoding so we are not
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107 | # stuck comparing hyphens with underscores in such things as iso-8859-1
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108 | my $normalized_filter = $filter_by_encoding;
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109 | $normalized_filter =~ s/[\W\_]//g;
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110 |
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111 | foreach my $lang (@{$self->{'languages'}}) {
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112 | my $normalized_lang = $lang;
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113 | $normalized_lang =~ s/[\W\_]//g;
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114 |
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115 | if($normalized_lang =~ m/$normalized_filter/i) {
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116 | push (@$languages, $lang);
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117 | }
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118 | }
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119 | }
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120 |
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121 | # if the filter_by_encoding wasn't in the list of language model filenames
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122 | # or if we're not filtering, then work with all language model filenames
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123 | if(scalar @$languages == 0) {
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124 | $languages = $self->{'languages'};
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125 | }
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126 |
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127 | my %results = ();
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128 | my $maxp = $self->{'opt_t'};
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129 |
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130 | # create ngrams for input.
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131 | my $unknown = $self->create_lm($inputref);
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132 |
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133 | foreach my $language (@$languages) {
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134 | # compare language model with input ngrams list
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135 | my ($i,$p)=(0,0);
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136 | while ($i < scalar (@$unknown)) {
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137 | if (defined ($self->{'ngrams'}->{$language}->{$unknown->[$i]})) {
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138 | $p=$p+abs($self->{'ngrams'}->{$language}->{$unknown->[$i]}-$i);
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139 | } else {
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140 | $p=$p+$maxp;
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141 | }
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142 | ++$i;
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143 | }
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144 | $results{$language} = $p;
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145 | }
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146 |
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147 | my @results = sort { $results{$a} <=> $results{$b} } keys %results;
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148 | my $a = $results{$results[0]};
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149 |
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150 | my @answers=(shift(@results));
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151 | while (@results && $results{$results[0]} < ($self->{'opt_u'} *$a)) {
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152 | @answers=(@answers,shift(@results));
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153 | }
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154 |
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155 | return \@answers;
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156 | }
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157 |
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158 |
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159 | # Same as below, but caches textcat results on filenames for subsequent use.
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160 | # The cache is a map of the filename to the corresponding filename_encodings
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161 | # (an array of results returned by textcat of the possible filename-encodings
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162 | # for the indexing filename string itself).
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163 | # Need to make sure that the filename is only the tailname: no path and no
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164 | # extension (no digits), in order to make optimum use of cached textcat.
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165 | # Textcat is performed on $filename_ref and the results associated with $filename_ref.
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166 | # The cache will be cleared when the max_cache_size is reached, which is
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167 | # MAX_CACHE_SIZE by default or can be specified as a parameter. The cache
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168 | # can also be cleared by a call to clear_filename_cache.
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169 | sub classify_cached_filename {
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170 | my ($self, $filename_ref)=@_;
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171 |
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172 | # if not already in the cache, work it out and put it there
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173 | if (!defined $filename_cache{$$filename_ref})
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174 | {
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175 | if (scalar (keys %filename_cache) >= $self->{'max_cache_size'}) {
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176 | $self->clear_filename_cache();
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177 | }
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178 | $filename_cache{$$filename_ref} = $self->classify($filename_ref);
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179 | }
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180 |
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181 | # return cached array of encodings for the given string
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182 | return $filename_cache{$$filename_ref};
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183 | }
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184 |
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185 | # Same as above, but caches textcat results on filecontents for subsequent use.
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186 | # Textcat on a file's contents to work out its possible encodings. Uses the cache.
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187 | # The cache is a map of the filename to an array of possible filename_encodings
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188 | # for the *contents* of the file returned by textcat.
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189 | # Textcat is performed on $contents_ref and the results associated with $filename.
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190 | # The cache will be cleared when the max_cache_size is reached, which is
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191 | # MAX_CACHE_SIZE by default or can be specified as a parameter. The cache
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192 | # can also be cleared by a call to clear_filecontents_cache.
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193 | sub classify_contents {
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194 | my ($self, $contents_ref, $filename)=@_;
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195 |
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196 | # if not already in the cache, work it out and put it there
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197 | if (!defined $filecontents_cache{$filename})
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198 | {
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199 | if (scalar (keys %filecontents_cache) >= $self->{'max_cache_size'}) {
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200 | $self->clear_filecontents_cache();
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201 | }
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202 |
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203 | # Finally, we can perform the textcat classification of language and encoding
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204 | $filecontents_cache{$filename} = $self->classify($contents_ref);
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205 | }
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206 | # return cached array of content encodings for the given filename
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207 | return $filecontents_cache{$filename};
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208 | }
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209 |
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210 |
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211 | # Given the known encoding for a file's contents, performs a textcat
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212 | # filtering on the languages for the given encoding. Results are stored
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213 | # in the cache TWICE: once under $filename|$filter_by_encoding, and
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214 | # once under the usual $filename, so that subsequent calls to either
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215 | # this method or classify_contents using the same filename will not
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216 | # perform textcat again.
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217 | sub classify_contents_for_encoding {
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218 | my ($self, $contents_ref, $filename, $filter_by_encoding)=@_;
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219 |
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220 | if (!defined $filecontents_cache{"$filename|$filter_by_encoding"})
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221 | {
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222 | if (scalar (keys %filecontents_cache) >= $self->{'max_cache_size'}) {
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223 | $self->clear_filecontents_cache();
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224 | }
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225 |
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226 | $filecontents_cache{"$filename|$filter_by_encoding"} = $self->classify($contents_ref, $filter_by_encoding);
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227 | # store this in cache again under $filename entry, so that subsequent
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228 | # calls to classify_contents will find it in the cache already
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229 | $filecontents_cache{$filename} = $self->classify($contents_ref, $filter_by_encoding);
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230 | }
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231 | return $filecontents_cache{$filename};
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232 | }
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233 |
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234 |
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235 | # This method returns the most frequently occurring encoding
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236 | # but only if any encoding occurs more than once in the given results.
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237 | # Otherwise, "" is returned.
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238 | sub most_frequent_encoding {
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239 | my ($self, $results) = @_;
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240 | my $best_encoding = "";
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241 |
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242 | # guessed_encodings is a hashmap of Encoding -> Frequency pairs
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243 | my %guessed_encodings = ();
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244 | foreach my $result (@$results) {
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245 | # Get the encoding portion of a language-model filename like en-iso8859_1
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246 | my ($encoding) = ($result =~ /^(?:[^\-]+)\-([^\-]+)$/);
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247 | if(!defined($guessed_encodings{$encoding})) {
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248 | $guessed_encodings{$encoding} = 0;
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249 | }
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250 | $guessed_encodings{$encoding}++;
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251 | }
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252 |
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253 | $guessed_encodings{""}=-1; # for default best_encoding of ""
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254 |
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255 | foreach my $enc (keys %guessed_encodings) {
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256 | if ($guessed_encodings{$enc} > $guessed_encodings{$best_encoding}) {
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257 | $best_encoding = $enc;
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258 | }
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259 | }
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260 |
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261 | # If best_encoding's frequency == 1, then the frequency for all encodings will
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262 | # be 1 since the sum total of all frequencies is num_results: if any encoding
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263 | # has frequency > 1 (it's possibly the best_encoding), one or more of the others
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264 | # would have been at 0 frequency to compensate.
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265 | return ($guessed_encodings{$best_encoding} > 1) ? $best_encoding : "";
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266 | }
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267 |
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268 |
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269 | # set some of the specific member variables
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270 | sub set_opts {
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271 | my ($self, $opt_freq, $opt_factor, $opt_top, $max_size_of_cache)=@_;
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272 |
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273 | $self->{'opt_f'} = $opt_freq if defined $opt_freq;
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274 | $self->{'opt_u'} = $opt_factor if defined $opt_factor;
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275 | $self->{'opt_t'} = $opt_top if defined $opt_top;
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276 |
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277 | $self->{'max_cache_size'} = $max_size_of_cache if defined $max_size_of_cache;
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278 | }
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279 |
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280 | sub get_opts {
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281 | my $self = shift (@_);
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282 | return ($self->{'opt_f'}, $self->{'opt_u'}, $self->{'opt_t'}, $self->{'max_cache_size'});
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283 | }
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284 |
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285 | # Clears the filename cache (a map of strings to the textcat results for each string).
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286 | sub clear_filename_cache {
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287 | my $self = shift (@_);
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288 |
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289 | %filename_cache = ();
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290 | }
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291 |
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292 | # Clears the filecontents cache (a map of filenames to the textcat results on the contents of each file).
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293 | sub clear_filecontents_cache {
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294 | my $self = shift (@_);
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295 |
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296 | %filecontents_cache = ();
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297 | }
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298 |
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299 | sub create_lm {
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300 | # $ngram contains reference to the hash we build
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301 | # then add the ngrams found in each word in the hash
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302 | my ($self, $textref) = @_;
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303 |
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304 | my $ngram = {};
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305 |
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306 | foreach my $word (split(/[$non_word_characters]+/, $$textref)) {
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307 | $word = "_" . $word . "_";
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308 | my $len = length($word);
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309 | my $flen=$len;
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310 | my $i;
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311 |
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312 | for ($i=0; $i<$flen; $i++) {
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313 | $ngram->{substr($word,$i,5)}++ if $len > 4;
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314 | $ngram->{substr($word,$i,4)}++ if $len > 3;
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315 | $ngram->{substr($word,$i,3)}++ if $len > 2;
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316 | $ngram->{substr($word,$i,2)}++ if $len > 1;
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317 | $ngram->{substr($word,$i,1)}++;
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318 | $len--;
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319 | }
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320 | }
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321 |
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322 | map { if ($ngram->{$_} <= $self->{'opt_f'}) { delete $ngram->{$_}; }
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323 | } keys %$ngram;
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324 |
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325 | # sort the ngrams, and spit out the $opt_t frequent ones.
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326 | # adding `or $a cmp $b' in the sort block makes sorting five
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327 | # times slower..., although it would be somewhat nicer (unique result)
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328 | my @sorted = sort { $ngram->{$b} <=> $ngram->{$a} } keys %$ngram;
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329 | splice(@sorted,$self->{'opt_t'}) if (@sorted > $self->{'opt_t'});
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330 | return \@sorted;
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331 | }
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332 |
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333 | 1;
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