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Natural Language Processing with Java and LingPipe Cookbook

You're reading from  Natural Language Processing with Java and LingPipe Cookbook

Product type Book
Published in Nov 2014
Publisher
ISBN-13 9781783284672
Pages 312 pages
Edition 1st Edition
Languages

Table of Contents (14) Chapters

Natural Language Processing with Java and LingPipe Cookbook
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Simple Classifiers 2. Finding and Working with Words 3. Advanced Classifiers 4. Tagging Words and Tokens 5. Finding Spans in Text – Chunking 6. String Comparison and Clustering 7. Finding Coreference Between Concepts/People Index

Using Lucene/Solr tokenizers with LingPipe


We can use these Lucene tokenizers with LingPipe; this is useful because Lucene has such a rich set of them. We are going to show how to wrap a Lucene TokenStream into a LingPipe TokenizerFactory by extending the Tokenizer abstract class.

How to do it...

We will shake things up a bit and have a recipe that is not interactive. Perform the following steps:

  1. Invoke the LuceneAnalyzerTokenizerFactory class from the command line:

    java -cp lingpipe-cookbook.1.0.jar:lib/lucene-analyzers-common-4.6.0.jar:lib/lucene-core-4.6.0.jar:lib/lingpipe-4.1.0.jar com.lingpipe.cookbook.chapter2.LuceneAnalyzerTokenizerFactory
    
  2. The main() method in the class specifies the input:

    String text = "Hi how are you? " + "Are the numbers 1 2 3 4.5 all integers?";
    Analyzer analyzer = new StandardAnalyzer(Version.LUCENE_46);
    TokenizerFactory tokFactory = new LuceneAnalyzerTokenizerFactory(analyzer, "DEFAULT");
    Tokenizer tokenizer = tokFactory.tokenizer(text.toCharArray(), 0, text.length...
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