# *********************************************** # # !!!! DO NOT EDIT !!!! # # This file was auto-generated by Build.PL. # # *********************************************** # # Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. =encoding utf8 =head1 NAME Lucy::Analysis::RegexTokenizer - Split a string into tokens. =head1 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 => [ $word_char_tokenizer, $normalizer, $stemmer ], ); =head1 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 C matching one token. If our source string is… "Eats, Shoots and Leaves." … then a “whitespace tokenizer” with a C of C<"\\S+"> produces… Eats, Shoots and Leaves. … while a “word character tokenizer” with a C of C<"\\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. =head1 CONSTRUCTORS =head2 new my $word_char_tokenizer = Lucy::Analysis::RegexTokenizer->new( pattern => '\w+', # required ); Create a new RegexTokenizer. =over =item * B - A string specifying a Perl-syntax regular expression which should match one token. The default value is C<\w+(?:[\x{2019}']\w+)*>, which matches “it’s” as well as “it” and “O’Henry’s” as well as “Henry”. =back =head1 METHODS =head2 transform my $inversion = $regex_tokenizer->transform($inversion); Take a single L as input and returns an Inversion, either the same one (presumably transformed in some way), or a new one. =over =item * B - An inversion. =back =head1 INHERITANCE Lucy::Analysis::RegexTokenizer isa L isa Clownfish::Obj. =cut