NAME¶

Lucy::Analysis::RegexTokenizer - Split a string into tokens.

SYNOPSIS¶

    my $whitespace_tokenizer
        = Lucy::Analysis::RegexTokenizer->new( pattern => '\S+' );
    # or...
    my $word_char_tokenizer
        = Lucy::Analysis::RegexTokenizer->new( pattern => '\w+' );
    # or...
    my $apostrophising_tokenizer = Lucy::Analysis::RegexTokenizer->new;
    # Then... once you have a tokenizer, put it into a PolyAnalyzer:
    my $polyanalyzer = Lucy::Analysis::PolyAnalyzer->new(
        analyzers => [ $case_folder, $word_char_tokenizer, $stemmer ], );

DESCRIPTION¶

Generically, "tokenizing" is a process of breaking up a string into an array of "tokens". For instance, the string "three blind mice" might be tokenized into "three", "blind", "mice". Lucy::Analysis::RegexTokenizer decides where it should break up the text based on a regular expression compiled from a supplied "pattern" matching one token. If our source string is...

    "Eats, Shoots and Leaves."

... then a "whitespace tokenizer" with a "pattern" of "\\S+" produces...

    Eats,
    Shoots
    and
    Leaves.

... while a "word character tokenizer" with a "pattern" of "\\w+" produces...

    Eats
    Shoots
    and
    Leaves

... the difference being that the word character tokenizer skips over punctuation as well as whitespace when determining token boundaries.

CONSTRUCTORS¶

new( [labeled params] )¶

    my $word_char_tokenizer = Lucy::Analysis::RegexTokenizer->new(
        pattern => '\w+',    # required
    );

•

pattern - A string specifying a Perl-syntax regular expression which should match one token. The default value is "\w+(?:[\x{2019}']\w+)*", which matches "it's" as well as "it" and "O'Henry's" as well as "Henry".

INHERITANCE¶

Lucy::Analysis::RegexTokenizer isa Lucy::Analysis::Analyzer isa Lucy::Object::Obj.