Mischa Spiegelmock > Algorithm-NGram-0.9 > Algorithm::NGram

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Module Version: 0.9   Source  

NAME ^

Algorithm::NGram

SYNPOSIS ^

    use Algorithm::NGram;
    my $ng = Algorithm::NGram->new(ngram_width => 3); # use trigrams

    # feed in text
    $ng->add_text($text1); # analyze $text1
    $ng->add_text($text2); # analyze $text2

    # feed in arbitrary sequence of tokens
    $ng->add_start_token;
    $ng->add_tokens(qw/token1 token2 token3/);
    $ng->add_end_token;

    my $output = $ng->generate_text;

DESCRIPTION ^

This is a module for analyzing token sequences with n-grams. You can use it to parse a block of text, or feed in your own tokens. It can generate new sequences of tokens from what has been fed in.

EXPORT ^

None.

METHODS ^

new

Create a new n-gram analyzer instance.

Options:

ngram_width

This is the "window size" of how many tokens the analyzer will keep track of. A ngram_width of two will make a bigram, a ngram_width of three will make a trigram, etc...

ngram_width

Returns token window size (e.g. the "n" in n-gram)

token_table

Returns n-gram table

add_text

Splits a block of text up by whitespace and processes each word as a token. Automatically calls add_start_token() at the beginning of the text and add_end_token() at the end.

add_tokens

Adds an arbitrary list of tokens.

add_start_token

Adds the "start token." This is useful because you often will want to mark the beginnings and ends of a token sequence so that when generating your output the generator will know what tokens start a sequence and when to end.

add_end_token

Adds the "end token." See add_start_token().

analyze

Generates an n-gram frequency table. Returns a hashref of N => tokens => count, where N is the number of tokens (will be from 2 to ngram_width). You will not normally need to call this unless you want to get the n-gram frequency table.

generate_text

After feeding in text tokens, this will return a new block of text based on whatever text was added.

generate

Generates a new sequence of tokens based on whatever tokens have previously been fed in.

next_tok

Given a list of tokens, will pick a possible token to come next.

token_lookup

Returns a hashref of the counts of tokens that follow a sequence of tokens.

token_key

Serializes a sequence of tokens for use as a key into the n-gram table. You will not normally need to call this.

serialize

Returns the tokens and n-gram (if one has been generated) in a string

deserialize($string)

Deserializes a string and returns an Algorithm::NGram instance

SEE ALSO ^

Text::Ngram, Text::Ngrams

AUTHOR ^

Mischa Spiegelmock, <mspiegelmock@gmail.com>

COPYRIGHT AND LICENSE ^

Copyright 2007 by Mischa Spiegelmock

This library is free software; you can redistribute it and/or modify it under the same terms as Perl itself.

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