KinoSearch::Analysis::Tokenizer - Split a string into tokens.
my $whitespace_tokenizer
= KinoSearch::Analysis::Tokenizer->new( pattern => '\S+' );
# or...
my $word_char_tokenizer
= KinoSearch::Analysis::Tokenizer->new( pattern => '\w+' );
# or...
my $apostrophising_tokenizer = KinoSearch::Analysis::Tokenizer->new;
# Then... once you have a tokenizer, put it into a PolyAnalyzer:
my $polyanalyzer = KinoSearch::Analysis::PolyAnalyzer->new(
analyzers => [ $lc_normalizer, $word_char_tokenizer, $stemmer ], );
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".
KinoSearch::Analysis::Tokenizer 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.
my $word_char_tokenizer = KinoSearch::Analysis::Tokenizer->new(
pattern => '\w+', # required
);
\w+(?:[\x{2019}']\w+)*, which matches "it's" as well as
"it" and "O'Henry's" as well as "Henry".
KinoSearch::Analysis::Tokenizer isa KinoSearch::Analysis::Analyzer isa KinoSearch::Obj.
Copyright 2005-2008 Marvin Humphrey
See KinoSearch version 0.20.