# (c) 2003-2017 Vlado Keselj http://web.cs.dal.ca/~vlado
#
# Text::Ngrams - A Perl module for N-grams processing
package Text::Ngrams;
use strict;
require Exporter;
use Carp;
use vars qw($VERSION @ISA @EXPORT @EXPORT_OK %EXPORT_TAGS);
@ISA = qw(Exporter);
%EXPORT_TAGS = ( 'all' => [ qw(new encode_S decode_S) ] );
@EXPORT_OK = ( @{ $EXPORT_TAGS{'all'} } );
@EXPORT = qw(new);
$VERSION = '2.006';
use vars qw($Version);
$Version = $VERSION;
use vars @EXPORT_OK;
use vars qw(); # non-exported package globals go here
sub new {
my $package = shift;
$package = ref($package) || $package;
my $self = {};
my (%params) = @_;
$self->{windowsize} = exists($params{windowsize}) ?
$params{windowsize} : 3;
die "nonpositive window size: $self->{windowsize}" unless $self->{windowsize} > 0;
delete($params{windowsize});
if (! exists($params{type}) or $params{type} eq 'character') {
$self->{skiprex} = '';
$self->{tokenrex} = qr/([a-zA-Z]|[^a-zA-Z]+)/;
$self->{processtoken} = sub { s/[^a-zA-Z]+/ /; $_ = uc $_ };
$self->{allow_iproc} = 1;
}
elsif ($params{type} eq 'utf8') {
$self->{skiprex} = '';
$self->{tokenrex} = qr/([\xF0-\xF4][\x80-\xBF][\x80-\xBF][\x80-\xBF]
|[\xE0-\xEF][\x80-\xBF][\x80-\xBF]
|[\xC2-\xDF][\x80-\xBF]
|[\x00-\xFF])/x;
$self->{processtoken} = '';
}
#MJ ->
#this type is analogous to the "character" type but defined for utf8 characters
elsif ($params{type} eq 'utf8_character') {
# $self->{inputlayer}
# input layer to be put on the input stream by the function binmode
# before reading from a given stream and to be removed by
# ***binmode HANDLE,":pop"*** after the reading from the particular
# stream is done has to be a real layer (like ":encoding(utf8)"), not a
# pseudo layer (like ":utf8") so that the psuedo layer ":pop" is able to
# remove this input layer
$self->{inputlayer} = ':encoding(utf8)';
# this will automatically decode input text from utf8 into Perl internal
# reporesentation of Unicode strings and so the regular expressions for
# Unicode as well as the uc function can be performed on them
$self->{skiprex} = '';
$self->{tokenrex} = qr/(\p{IsAlpha}|\P{IsAlpha}+)/;
$self->{processtoken} = sub { s/\P{IsAlpha}+/ /; $_ = uc $_ ;
$_ = Encode::encode_utf8( $_ ); };
# the last operation ***$_=Encode::encode_utf8( $_ )*** is necessary
# to go back to utf8 encoding from the internal Perl representation
# so that for the output the n-grams are in utf8 (encoded by encode_S though)
$self->{allow_iproc} = 0;
# allow_iproc has to be 0. Otherwise the last token in the read block will
# be preprocessed and encoded in utf8,
# and then attached at the beginning of the next block read from input,
# which will be in the internal Perl representation
}
#MJ <-
elsif ($params{type} eq 'byte') {
$self->{skiprex} = '';
$self->{tokenrex} = '';
$self->{processtoken} = '';
}
elsif ($params{type} eq 'word') {
$self->{skiprex} = qr/[^a-zA-Z0-9]+/;
$self->{skipinsert} = ' ';
$self->{tokenrex} = qr/([a-zA-Z]+|(\d+(\.\d+)?|\d*\.\d+)([eE][-+]?\d+)?)/;
$self->{processtoken} = sub { s/(\d+(\.\d+)?|\d*\.\d+)([eE][-+]?\d+)?/<NUMBER>/ }
}
else { die "unknown type: $params{type}" }
delete($params{type});
$self->{'table'} = [ ];
$self->{'total'} = [ ];
$self->{'total_distinct_count'} = 0;
$self->{'lastngram'} = [ ];
$self->{'next_token_id'} = 0;
$self->{'token_dict'} = { };
$self->{'token_S'} = [ ];
$self->{'token'} = [ ];
foreach my $i ( 1 .. $self->{windowsize} ) {
$self->{table}[$i] = { };
$self->{total}[$i] = 0;
$self->{firstngram}[$i] = '';
$self->{lastngram}[$i] = '';
}
if (exists($params{'limit'})) {
die "limit=$params{'limit'}" if $params{'limit'} < 1;
$self->{'limit'} = $params{'limit'};
}
delete($params{'limit'});
die "unknown parameters:".join(' ', %params) if %params;
bless($self, $package);
return $self;
}
sub feed_tokens {
my $self = shift;
# count all n-grams sizes starting from max to 1
foreach my $t1 (@_) {
my $t = $t1;
if (defined($self->{token_dict}->{$t})) {
$t = $self->{token_dict}->{$t};
} else {
my $id = $self->{next_token_id}++;
$self->{token_S}->[$id] = &encode_S($t);
$self->{token}->[$id] = $t;
$t = $self->{token_dict}->{$t} = $id;
}
for (my $n=$self->{windowsize}; $n > 0; $n--) {
if ($n > 1) {
next unless $self->{lastngram}[$n-1] ne '';
$self->{lastngram}[$n] = $self->{lastngram}[$n-1] .
' ' . $t;
} else { $self->{lastngram}[$n] = $t }
if ( ($self->{table}[$n]{$self->{lastngram}[$n]} += 1)==1)
{ $self->{'total_distinct_count'} += 1 }
$self->{'total'}[$n] += 1;
if ($self->{'firstngram'}[$n] eq '')
{ $self->{'firstngram'}[$n] = $self->{lastngram}[$n] }
}
}
if (exists($self->{'limit'}) and
$self->{'total_distinct_count'} > 2 * $self->{'limit'})
{ $self->_reduce_to_limit }
}
sub process_text {
my $self = shift;
$self->_process_text(0, @_);
if (exists($self->{'limit'})) { $self->_reduce_to_limit }
}
sub _process_text {
my $self = shift;
my $cont = shift; # the minimal number of chars left for
# continuation (the new-line problem, and the
# problem with too long lines)
# The remainder of unprocessed string is
# returned.
if ($cont < 0) { $cont = 0 }
if ( # type is byte
$self->{skiprex} eq '' and
$self->{tokenrex} eq '' and
$self->{processtoken} eq '' and
$cont == 0
)
{ return $self->_process_text_byte(@_) }
my (@tokens);
my $text;
while (@_) {
$text .= shift @_;
while (length($text) > 0) {
my $textl = $text;
my $skip = '';
if ($self->{skiprex} ne '' && $textl =~ /^$self->{skiprex}/)
{ $skip = $&; $textl = $'; }
if (defined($self->{skipinsert})) {
$skip = $self->{skipinsert};
$text = $skip.$textl;
}
if (length($textl) < $cont) { last }
if (length($textl)==0) { $text=$textl; last; }
local $_;
if ($self->{tokenrex} ne '') {
if ($textl =~ /^$self->{tokenrex}/)
{ $_ = $&; $textl = $'; }
}
else
{ $_ = substr($textl, 0, 1); $textl = substr($textl, 1) }
last if $_ eq '';
if (length($textl) < $cont) {
if (defined($self->{allow_iproc}) && $self->{allow_iproc}
&& ref($self->{processtoken}) eq 'CODE')
{ &{$self->{processtoken}} }
$text = $skip.$_.$textl;
last;
}
if (ref($self->{processtoken}) eq 'CODE')
{ &{$self->{processtoken}} }
push @tokens, $_;
$text = $textl;
}
}
$self->feed_tokens(@tokens);
return $text;
}
sub _process_text_byte {
my $self = shift;
for (my $i=0; $i<=$#_; ++$i) {
my @a = split('', $_[$i]);
next if $#a==-1;
$self->feed_tokens( @a );
}
return '';
}
sub process_files {
my $self = shift;
#MJ ->
my $input_layer='';
if (defined($self->{inputlayer})) {$input_layer=$self->{inputlayer};}
#MJ <-
foreach my $f (@_) {
my $f1;
local *F;
if (not ref($f))
{ open(F, "$f") or die "cannot open $f:$!"; $f1 = *F }
else { $f1 = $f }
binmode $f1; # avoid text mode
#MJ ->
#put the encoding layer on the input when requested
if ($input_layer ne '') {
binmode $f1, $input_layer;
}
#MJ <-
my ($text, $text_l, $cont) = ('', 0, 1);
if ( # type is byte
$self->{skiprex} eq '' and
$self->{tokenrex} eq '' and
$self->{processtoken} eq ''
)
{ $cont = 0 }
while (1) {
$text_l = length($text);
read($f1, $text, 1024, length($text));
last if length($text) <= $text_l;
$text = $self->_process_text($cont, $text);
}
$text = $self->_process_text(0, $text);
#MJ ->
#remove the encoding layer from the input stream if it was added
#Caution: here is what the Perl documentation says about the pseudo layer ":pop"
#"Should be considered as experimental. (...) A more elegant (and safer) interface is needed."
if ($input_layer ne '') {
binmode $f1,":pop";
}
#MJ <-
close($f1) if not ref($f);
if (exists($self->{'limit'})) { $self->_reduce_to_limit }
}
}
sub _reduce_to_limit {
my $self = shift;
return unless exists($self->{'limit'}) and
$self->{'limit'} > 0;
while ($self->{'total_distinct_count'} > $self->{'limit'}) {
my $nextprunefrequency = 0;
for (my $prunefrequency=1;; $prunefrequency = $nextprunefrequency) {
$nextprunefrequency = $self->{'total'}[1];
foreach my $n (1 .. $self->{'windowsize'}) {
my @keys = keys(%{$self->{table}[$n]});
foreach my $ngram (@keys) {
my $f = $self->{table}[$n]{$ngram};
if ($f <= $prunefrequency) {
delete $self->{'table'}[$n]{$ngram};
$self->{'total'}[$n] -= $prunefrequency;
$self->{'total_distinct_count'} -= 1;
}
elsif ($nextprunefrequency > $f)
{ $nextprunefrequency = $f }
}
return if $self->{'total_distinct_count'} <= $self->{'limit'};
die if $nextprunefrequency <= $prunefrequency;
} } } }
# Sorts keys according to the lexicographic order.
sub _keys_sorted {
my $self = shift;
my $n = shift;
my @k = keys(%{$self->{table}[$n]});
my %k1 = ();
foreach my $k (@k) {
$k1{
join (' ', map { $self->{token}->[$_] } split(/ /, $k) )
} = $k;
}
@k = ();
foreach my $k (sort(keys(%k1))) {
push @k, $k1{$k};
}
return @k;
}
sub get_ngrams {
my $self = shift;
my (%params) = @_;
my $n = exists($params{'n'})? $params{'n'} : $self->{windowsize};
my $onlyfirst = exists($params{'onlyfirst'}) ? $params{'onlyfirst'} : '';
my $opt_normalize = exists($params{'normalize'}) ?$params{'normalize'} : '';
my $total = $self->{total}[$n]; my @keys = ();
if (!exists($params{'orderby'}) or $params{'orderby'} eq 'ngram') {
@keys = $self->_keys_sorted($n);
} elsif ($params{'orderby'} eq 'none') {
die "onlyfirst requires order" if $onlyfirst;
@keys = keys(%{$self->{table}[$n]})
}
elsif ($params{'orderby'} eq 'frequency') {
@keys = $self->_keys_sorted($n);
my %keysord = ();
for (my $i=0; $i<=$#keys; ++$i) { $keysord{$keys[$i]} = $i }
@keys = sort { $self->{table}[$n]{$b} <=> $self->{table}[$n]{$a}
or $keysord{$a} <=> $keysord{$b} }
keys(%{$self->{table}[$n]});
}
else { die }
@keys = splice(@keys,0,$onlyfirst) if $onlyfirst;
my @ret;
foreach my $ngram (@keys) {
my $count = $self->{table}[$n]{$ngram};
$count = ($opt_normalize ? ($count / $total ) : $count);
push @ret, $self->_encode_S($ngram), $count;
}
return @ret;
}
sub to_string {
my $self = shift;
my (%params) = @_;
my $n = exists($params{'n'})? $params{'n'} : $self->{windowsize};
my $onlyfirst = exists($params{'onlyfirst'}) ? $params{'onlyfirst'} : '';
my $opt_normalize = exists($params{'normalize'}) ?$params{'normalize'} : '';
#my $onlyfirst = exists($params{'onlyfirst'}) ?
#$params{'onlyfirst'} : '';
#delete $params{'onlyfirst'};
my $out = exists($params{'out'}) ? $params{'out'} : '';
delete $params{'out'};
my $outh = $out;
if ($out and (not ref($out))) {
local *FH; open(FH, ">$out") or die "cannot open $out:$!";
$outh = *FH;
}
#my $opt_normalize = $params{'normalize'};
#delete $params{'normalize'};
my $spartan = $params{'spartan'};
delete $params{'spartan'};
my $ret='';
$ret = "BEGIN OUTPUT BY Text::Ngrams version $VERSION\n\n" unless $spartan;
foreach my $n (1 .. $self->{windowsize}) {
if ($spartan and $n < $self->{windowsize}) { next }
if (! $spartan ) {
my $tmp = "$n-GRAMS (total count: $self->{total}[$n])";
$ret .= "$tmp\n" .
"FIRST N-GRAM: ". $self->_encode_S($self->{firstngram}[$n]).
"\n LAST N-GRAM: ".$self->_encode_S($self->{lastngram}[$n])."\n".
('-' x length($tmp)) . "\n";
}
my $total = $self->{total}[$n];
my @keys;
if (!exists($params{'orderby'}) or $params{'orderby'} eq 'ngram')
{ @keys = $self->_keys_sorted($n) }
elsif ($params{'orderby'} eq 'none') {
die "onlyfirst requires order" if $onlyfirst;
@keys = keys(%{$self->{table}[$n]})
}
elsif ($params{'orderby'} eq 'frequency') {
@keys = sort { $self->{table}[$n]{$b} <=>
$self->{table}[$n]{$a} }
keys(%{$self->{table}[$n]});
}
else { die }
@keys = splice(@keys,0,$onlyfirst) if $onlyfirst;
my %params1=%params; $params1{n}=$n;
my @a = $self->get_ngrams(%params1);
for (my $i=0; $i<=$#a; $i+=2) {
my $ng = $a[$i]; my $f = $a[$i+1];
$ret.="$ng\t$f\n";
}
if ($out) { print $outh $ret; $ret = '' }
$ret .= "\n" unless $spartan;
}
$ret .= "END OUTPUT BY Text::Ngrams\n" unless $spartan;
if ($out) {
print $outh $ret; $ret = '';
close($outh) if not ref($out);
}
return $ret;
}
# http://web.cs.dal.ca/~vlado/srcperl/snip/decode_S
sub decode_S ( $ ) {
local $_ = shift;
my $out;
while (length($_) > 0) {
if (/^\\(\S)/) {
$_ = $'; my $tmp = $1;
$tmp =~ tr/0-5Aabtnvfroil6-9NSTcEseFGRUd/\x00-\x1F\x7F/;
$out .= $tmp;
}
elsif (/^\^_/) { $_ = $'; $out .= "\240" }
elsif (/^\^(\S)/) { $_ = $'; $out .= pack('C',ord($1)+128); }
elsif (/^\`(\S)/) {
$_ = $'; my $tmp = $1;
$tmp =~ tr/0-5Aabtnvfroil6-9NSTcEseFGRUd/\x00-\x1F\x7F/;
$out .= pack('C', ord($tmp)+128);
}
elsif (/^_+/) { $_ = $'; my $tmp = $&; $tmp =~ tr/_/ /; $out .= $tmp; }
elsif (/^[^\\^\`\s_]+/) { $_ = $'; $out .= $&; }
else { die "decode_S unexpected:$_" }
}
return $out;
}
sub _encode_S {
my $self = shift;
my @r = ();
while (@_) {
push @r,
map { $self->{token_S}->[$_] } split(/ /, shift @_);
}
return join(' ', @r);
}
# http://www.cs.dal.ca/~vlado/srcperl/snip/encode_S
sub encode_S( $ ) {
local $_ = shift;
s/=/=0/g; # first hide a special character (=)
s/\\/=b/g; # encode backslashes
s/([\x80-\xFF])/=x$1/g; # replace >127 with 127
tr/\x80-\xFF/\x00-\x7F/;
s/=x=/=X/g; # hide again =
s/([\x00-\x1F\x5C\x5E-\x60\x7F])/=B$1/g;
tr/\x20\x00-\x1F\x7F/_0-5Aabtnvfroil6-9NSTcEseFGRUd/;
s/=x=B(\S)/`$1/g; # hex backslash
s/=x(\S)/^$1/g; # hex other
s/=B(\S)/\\$1/g; # backslashed
s/=b/\\\\/g; # original backslashes
s/=X/^=0/g;
s/=0/=/g; # put back =
return $_;
}
1;
__END__
=head1 NAME
Text::Ngrams - Flexible Ngram analysis (for characters, words, and more)
=head1 SYNOPSIS
For default character n-gram analysis of string:
use Text::Ngrams;
my $ng = Text::Ngrams->new;
$ng->process_text('abcdefg1235678hijklmnop');
print $ng3->to_string;
my @ngramsarray = $ng->get_ngrams;
# or put ngrams and frequencies into a hash
my %ngrams = $ng3->get_ngrams( n => 3, normalize => 1 );
One can also feed tokens manually:
use Text::Ngrams;
my $ng3 = Text::Ngrams->new;
$ng3->feed_tokens('a');
$ng3->feed_tokens('b');
$ng3->feed_tokens('c', 'd');
$ng3->feed_tokens(qw(e f g h));
We can choose n-grams of various sizes, e.g.:
my $ng = Text::Ngrams->new( windowsize => 6 );
or different types of n-grams, e.g.:
my $ng = Text::Ngrams->new( type => byte );
my $ng = Text::Ngrams->new( type => word );
my $ng = Text::Ngrams->new( type => utf8 );
To process a list of files:
$ng->process_files('somefile.txt', 'otherfile.txt');
To read the standard input or another file handle:
$ng->process_files(\*STDIN);
To read a file named file.txt and create a profile file file.profile
of 100 most frequent, normalized byte tri-grams:
use Text::Ngrams;
my $ng = Text::Ngrams->new( windowsize => 3, type => byte );
$ng->process_files("file.txt");
$ng->to_string( orderby=>'frequency', onlyfirst=>100,
out => "file.profile", normalize=>1,
spartan=>1);
=head1 DESCRIPTION
This module implement text n-gram analysis, supporting several types of
analysis, including character and word n-grams.
The module Text::Ngrams is very flexible. For example, it allows a user
to manually feed a sequence of any tokens. It handles several types of tokens
(character, word), and also allows a lot of flexibility in automatic
recognition and feed of tokens and the way they are combined in an n-gram.
It counts all n-gram frequencies up to the maximal specified length.
The output format is meant to be pretty much human-readable, while also
loadable by the module.
The module can be used from the command line through the script
C<ngrams.pl> provided with the package.
=head1 OUTPUT FORMAT
The output looks like this (version number may be different):
BEGIN OUTPUT BY Text::Ngrams version 2.004
1-GRAMS (total count: 8)
------------------------
a 1
b 1
c 1
d 1
e 1
f 1
g 1
h 1
2-GRAMS (total count: 7)
------------------------
ab 1
bc 1
cd 1
de 1
ef 1
fg 1
gh 1
3-GRAMS (total count: 6)
------------------------
abc 1
bcd 1
cde 1
def 1
efg 1
fgh 1
END OUTPUT BY Text::Ngrams
N-grams are encoded using encode_S
(F<web.cs.dal.ca/~vlado/srcperl/snip/encode_S>), so that they can
always be recognized as \S+. This encoding does not change strings
"too much", e.g., letters, digits, and most punctuation characters
will remail unchanged, and space is replaced by underscore (_).
However, all bytes (even with code greater than 127) are encoded in
unambiguous and relatively compact way. Two functions, encode_S and
decode_S, are provided for translating arbitrary string into this form
and vice versa.
An example of word n-grams containing space:
BEGIN OUTPUT BY Text::Ngrams version 2.004
1-GRAMS (total count: 8)
------------------------
The 1
brown 3
fox 3
quick 1
2-GRAMS (total count: 7)
------------------------
The_brown 1
brown_fox 2
brown_quick 1
fox_brown 2
quick_fox 1
END OUTPUT BY Text::Ngrams
Or, in case of byte type of processing:
BEGIN OUTPUT BY Text::Ngrams version 2.004
1-GRAMS (total count: 55)
-------------------------
\t 3
\n 3
_ 12
, 2
. 3
T 1
b 3
c 1
... etc
2-GRAMS (total count: 54)
-------------------------
\t_ 1
\tT 1
\tb 1
\n\t 2
__ 5
_. 1
_b 2
_f 3
_q 1
,\n 2
.\n 1
.. 2
Th 1
br 3
ck 1
e_ 1
... etc
END OUTPUT BY Text::Ngrams
=head1 METHODS
=head2 new ( windowsize => POS_INTEGER, type => 'character' | 'byte' | 'word' | 'utf8' | 'utf8_character', limit => POS_INTEGER )
my $ng = Text::Ngrams->new;
my $ng = Text::Ngrams->new( windowsize=>10 );
my $ng = Text::Ngrams->new( type=>'word' );
my $ng = Text::Ngrams->new( limit=>10000 );
and similar.
Creates a new C<Text::Ngrams> object and returns it.
Parameters:
=over 4
=item limit
Limit the number of distinct n-grams collected during processing. Processing large files may be
slow, so you can limit the total number of distinct n-grams which are
counted to speed up processing. The speed-up is implemented by periodically prunning the
collected n-gram. Due to this process, the final n-gram counts may not be correct, and
the list of final most frequen n-grams may not be correct either.
B<BEWARE:> If a limit is set, the n-gram counts at the end may not be
correct due to periodical pruning of n-grams.
=item windowsize
n-gram size (i.e., `n' itself). Default is 3
if not given. It is stored in $object->{windowsize}.
=item type
Specifies a predefined type of n-grams:
=over 4
=item character (default)
Default character n-grams:
Read letters, sequences of all other characters are replaced
by a space, letters are turned uppercase.
=item byte
Raw character n-grams:
Don't ignore any bytes and don't pre-process them.
=item utf8
UTF8 characters: Variable length encoding.
=item word
Default word n-grams:
One token is a word consisting of letters, digits and decimal digit
are replaced by <NUMBER>, and everything else is ignored. A space is inserted
when n-grams are formed.
=item utf8_character
UTF8 analogue of the "character" type: from a UTF8 encoded text reads letters,
sequences of all other characters are replaced by a space, letters are turned uppercase
=back
One can also modify type, creating its own type, by fine-tuning several parameters
(they can be undefined):
$o->{skiprex} - regular expression for ignoring stuff between tokens.
$o->{skipinsert} - string to replace a skiprex match that makes
string too short (efficiency issue)
$o->{tokenrex} - regular expression for recognizing a token. If it is
empty, it means chopping off one character.
$o->{processtoken} - routine for token preprocessing. Token is given and returned in $_.
$o->{allow_iproc} - boolean, if set to true (1) allows for incomplete
tokens to be preprocessed and put back (efficiency motivation)
$o->{inputlayer} - input layer to be put on the input stream by the function binmode
before reading from a given stream and to be removed by ***binmode HANDLE,":pop"***
after the reading from the particular stream is done.
Has to be a real layer (like ":encoding(utf8)"), not a pseudo layer (like ":utf8")
so that the psuedo layer ":pop" is able to remove this input layer
For example, the types character, byte, and word are defined in the
foolowing way:
if ($params{type} eq 'character') {
$self->{skiprex} = '';
$self->{tokenrex} = qr/([a-zA-Z]|[^a-zA-Z]+)/;
$self->{processtoken} = sub { s/[^a-zA-Z]+/ /; $_ = uc $_ }
$self->{allow_iproc} = 1;
}
elsif ($params{type} eq 'byte') {
$self->{skiprex} = '';
$self->{tokenrex} = '';
$self->{processtoken} = '';
}
elsif ($params{type} eq 'utf8') {
$self->{skiprex} = '';
$self->{tokenrex} =
qr/([\xF0-\xF4][\x80-\xBF][\x80-\xBF][\x80-\xBF]
|[\xE0-\xEF][\x80-\xBF][\x80-\xBF]
|[\xC2-\xDF][\x80-\xBF]
|[\x00-\xFF])/x;
$self->{processtoken} = '';
}
elsif ($params{type} eq 'word') {
$self->{skiprex} = qr/[^a-zA-Z0-9]+/;
$self->{skipinsert} = ' ';
$self->{tokenrex} =
qr/([a-zA-Z]+|(\d+(\.\d+)?|\d*\.\d+)([eE][-+]?\d+)?)/;
$self->{processtoken} = sub
{ s/(\d+(\.\d+)?|\d*\.\d+)([eE][-+]?\d+)?/<NUMBER>/ }
}
=back
=head2 feed_tokens ( list of tokens )
$ng3->feed_tokens('a');
$ng3->feed_tokens('b', 'c');
This function supplies tokens directly.
=head2 process_text ( list of strings )
$ng3->process_text('abcdefg1235678hijklmnop');
$ng->process_text('The brown quick fox, brown fox, brown fox ...');
Process text, i.e., break each string into tokens and feed them.
=head2 process_files ( file_names or file_handle_references)
A usage example:
$ng->process_files('somefile.txt');
This method is used to process one or more files, similarly to processing text.
The files are processed line by line, so there should be no multi-line tokens.
Instead of filenames we can also give as arguments file handle references
when a file is already open. In this way, we can use the standard input handle as in:
$ng->process_files(\*STDIN);
=head2 get_ngrams ( n => NUMBER, orderby => 'ngram|frequency|none', onlyfirst => NUMBER, out => filename|handle,normalize=>1)
Returns an array of requested n-grams and their friequencies in order
(ngram1, f1, ngram2, f2, ...). The use of parameters is identical to
the function C<to_string>, except that the option 'spartan' is not applicable to C<get_ngrams> function.
Parameters:
=over 4
=item C<n>
The parameter C<n> specifies the size of n-grams being retrieved. The default value
is the C<windowsize> field. It should be less or equal than C<windowsize>.
=back
=head2 to_string ( orderby => 'ngram|frequency|none', onlyfirst => NUMBER, out => filename|handle, normalize => 1, spartan => 1 )
Some examples:
print $ng3->to_string;
print $ng->to_string( orderby=>'frequency' );
print $ng->to_string( orderby=>'frequency', onlyfirst=>10000 );
print $ng->to_string( orderby=>'frequency', onlyfirst=>10000,
normalize=>1 );
Produce string representation of the n-gram tables.
Parameters:
=over 4
=item C<orderby>
The parameter C<orderby> specifies the order of n-grams. The default
value is 'ngram'.
=item C<onlyfirst>
The parameter C<onlyfirst> causes printing only this many first n-grams
for each n. It is incompatible with C<orderby=>'none'>.
=item C<out>
The method C<to_string> produces n-gram tables. However, if those
tables are large and we know that we will write them to a file
right after processing, it may save memory and time to provide the
parameter C<out>, which is a filename or reference to a file handle.
(Experiments on my machine do not show significant improvement nor degradation.)
Filename will be opened and closed, while the file handle will not.
=item C<normalize>
This is a boolean parameter. By default, it is false (''), in which
case n-gram counts are produced. If it is true (e.g., 1), the output
will contain normalized frequencies; i.e., n-gram counts divided by
the total number of n-grams of the same size.
=item C<spartan>
This is a boolean parameter. By default, it is false (''), in which
case n-grams for n=1 up to the maximal value are printed. If it is
true, only a list of the most frequent n-grams with the maximal length
is printed.
=back
=head2 encode_S ( string )
This function translates any string in a /^\S*$/ compliant representation.
It is primarely used in n-grams string representation to prevent white-space
characters to invalidate the output format. A usage example is:
$e = Text::Ngrams::encode_S( $s );
or simply
$e = encode_S($s);
if encode_S is imported. Encodes arbitrary string into an \S* form.
See F<http://web.cs.dal.ca/~vlado/srcperl/snip/encode_S> for detailed
explanation.
=head2 decode_S ( string )
This is the inverse funcation of C<encode_S>. A usage example is:
$e = Text::Ngrams::decode_S( $s );
or simply
$e = decode_S($s);
if decode_S is imported. Decodes a string encoded in the \S* form.
See F<http://www.cs.dal.ca/~vlado/srcperl/snip/encode_S> for detailed
explanation.
=head1 PERFORMANCE
The preformance can vary a lot depending on the type of file, in
particular on the content entropy. For example a file in English is
processed faster than a file in Chinese, due to a larger number of
distinct n-grams.
The following tests are preformed on a Pentium-III 550MHz, 512MB
memory, Linux Red Hat 6 platform. (See C<ngrams.pl> - the script is
included in this package.)
ngrams.pl --n=10 --type=byte 1Mfile
The 1Mfile is a 1MB file of Chinese text. The program spent
consistently 20 sec per 100KB, giving 200 seconds (3min and 20sec) for
the whole file. However, after 4 minutes I gave up on waiting for
n-grams to be printed. The bottleneck seems to be encode_S function,
so after:
ngrams.pl -n=10 --type=byte --orderby=frequency --onlyfirst=5000
1Mfile
it took about 3:24 + 5 =~ 9 minutes to print. After changing
C<ngrams.pl> so that it provides parameter C<out> to C<to_string> in
module C<Ngrams.pm> (see Text::Ngrams), it still took:
3:09+1:28+4:40=9.17.
=head1 LIMITATIONS
The method C<process_file> does not handle multi-line tokens by default.
This can be fixed, but it does not seem to be worth the code
complication. There are various ways around this if one really needs
such tokens: One way is to preprocess them. Another way is to read
as much text as necessary at a time then to use C<process_text>, which
does handle multi-line tokens.
=head1 THANKS
I would like to thank cpan-testers, Jost Kriege, Shlomo Yona, David
Allen (for localizing and reporting and efficiency issue with ngram
prunning), Andrija, Roger Zhang, Jeremy Moses, Kevin J. Ziese, Hassen
Bouzgou, Michael Ricie, and Jingyi Yang for bug reports and comments.
Thanks to Chris Jordan for providing initial implementation of the
function get_strings (2005).
Thanks to Magdalenda Jankowska for implementing a new ngrams type
utf8_character, which is very useful in processing non-English text;
and for a bug fix.
I will be grateful for comments, bug reports, or just letting me know
that you used the module.
=head1 AUTHOR
Author:
2003-2017 Vlado Keselj http://web.cs.dal.ca/~vlado
Contributors:
2005 Chris Jordan (contributed initial get_ngrams method)
2012 Magdalena Jankowska (utf8_character ngrams type)
This module is provided "as is" without expressed or implied warranty.
This is free software; you can redistribute it and/or modify it under
the same terms as Perl itself.
To acknowledge the use of this module in academic publications, please use
a reference to the following paper:
N-gram-based Author Profiles for Authorship Attribution.
Vlado Keselj, Fuchun Peng, Nick Cercone, and Calvin Thomas. In Proceedings of
the Conference Pacific Association for Computational Linguistics, PACLING'03,
Dalhousie University, Halifax, Nova Scotia, Canada, pp. 255-264, August 2003.
http://web.cs.dal.ca/~vlado/papers/meta/Kes03.html
The latest version can be found at F<http://web.cs.dal.ca/~vlado/srcperl/>.
=head1 HISTORY
This code originated in my "monkeys and rhinos" project in 2000, and
is related to authorship attribution project. After our papers on authorship
attribution it was reformatted as a Perl module in 2003.
=head1 SEE ALSO
Some of the similiar projects and related resources are the following:
=over 4
=item Ngram Statistics Package in Perl, by T. Pedersen at al.
This is a package that includes a script for word n-grams.
=item Text::Ngram Perl Package by Simon Cozens
This is another CPAN package similar to Text::Ngrams for character n-grams.
As an XS implementation it is supposed to be very efficient.
=item Perl script ngram.pl by Jarkko Hietaniemi
This is a script for analyzing character n-grams.
=item Waterloo Statistical N-Gram Language Modeling Toolkit, in C++ by Fuchun Peng
A n-gram language modeling package written in C++.
=item CPAN N-gram module comparison article by Ben Bullock.
The page is available
at F<http://www.lemoda.net/perl/cpan-n-gram-modules/> gives an interesting list of
modules, although the review seem to be superficial and only partially correct.
The following modules are listed in this review:
Algorithm::NGram, IDS::Algorithm::Ngram, Lingua::EN::Bigram, Linuga::EN::Ngram,
Lingua::Gram, Lingua::Identify, Text::Mining::Algorithm::Ngram,
Text::Ngram, Text::Ngram::LanguageDetermine, Text::Ngramize, Ntext::Ngrams, and
Text::Positional::Ngram.
=back
Some links to these resources should be available at F<http://web.cs.dal.ca/~vlado/nlp>.
=cut
# $Id: $