org.apache.lucene.analysis.compound.package-info Maven / Gradle / Ivy

Go to download
Show more of this group Show more artifacts with this name
Show all versions of lucene-analyzers-common Show documentation
Additional Analyzers
The newest version!
/*
 * 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.
 */

/**
 * A filter that decomposes compound words you find in many Germanic
 * languages into the word parts. This example shows what it does:
 * 
 *  
 *   
 *  
 *  
 *   
 *  
 * Input token stream
Rindfleischüberwachungsgesetz Drahtschere abba
 * 

 * 
 *  
 *   
 *  
 *  
 *   
 *  
 *  
 *   
 *  
 *  
 *   
 *  
 *  
 *   
 *  
 *  
 *   
 *  
 *  
 *   
 *  
 *  
 *   
 *  
 *  
 *   
 *  
 *  
 *   
 *  
 * Output token stream
(Rindfleischüberwachungsgesetz,0,29)
(Rind,0,4,posIncr=0)
(fleisch,4,11,posIncr=0)
(überwachung,11,22,posIncr=0)
(gesetz,23,29,posIncr=0)
(Drahtschere,30,41)
(Draht,30,35,posIncr=0)
(schere,35,41,posIncr=0)
(abba,42,46)
 * 
 * The input token is always preserved and the filters do not alter the case of word parts. There are two variants of the
 * filter available:
 * 
 *  HyphenationCompoundWordTokenFilter: it uses a
 *  hyphenation grammar based approach to find potential word parts of a
 *  given word.
 *  DictionaryCompoundWordTokenFilter: it uses a
 *  brute-force dictionary-only based approach to find the word parts of a given
 *  word.
 * 
 * 
 * Compound word token filters
 * HyphenationCompoundWordTokenFilter
 * The {@link
 * org.apache.lucene.analysis.compound.HyphenationCompoundWordTokenFilter
 * HyphenationCompoundWordTokenFilter} uses hyphenation grammars to find
 * potential subwords that a worth to check against the dictionary. It can be used
 * without a dictionary as well but then produces a lot of "nonword" tokens.
 * The quality of the output tokens is directly connected to the quality of the
 * grammar file you use. For languages like German they are quite good.
 * Grammar file
 * Unfortunately we cannot bundle the hyphenation grammar files with Lucene
 * because they do not use an ASF compatible license (they use the LaTeX
 * Project Public License instead). You can find the XML based grammar
 * files at the
 * Objects
 * For Formatting Objects
 * (OFFO) Sourceforge project (direct link to download the pattern files:
 * http://downloads.sourceforge.net/offo/offo-hyphenation.zip
 * ). The files you need are in the subfolder
 * offo-hyphenation/hyph/
 * .
 * 

 * Credits for the hyphenation code go to the
 * Apache FOP project
 * .
 * 
 * DictionaryCompoundWordTokenFilter
 * The {@link
 * org.apache.lucene.analysis.compound.DictionaryCompoundWordTokenFilter
 * DictionaryCompoundWordTokenFilter} uses a dictionary-only approach to
 * find subwords in a compound word. It is much slower than the one that
 * uses the hyphenation grammars. You can use it as a first start to
 * see if your dictionary is good or not because it is much simpler in design.
 * 
 * Dictionary
 * The output quality of both token filters is directly connected to the
 * quality of the dictionary you use. They are language dependent of course.
 * You always should use a dictionary
 * that fits to the text you want to index. If you index medical text for
 * example then you should use a dictionary that contains medical words.
 * A good start for general text are the dictionaries you find at the
 * OpenOffice
 * dictionaries
 * Wiki.
 * 
 * Which variant should I use?
 * This decision matrix should help you:
 * 
 *  
 *   
 *   
 *   
 *  
 *  
 *   
 *   
 *   
 *  
 *  
 *   
 *   
 *   
 *  
 * Token filter Output quality Performance
HyphenationCompoundWordTokenFilter good if grammar file is good – acceptable otherwise fast
DictionaryCompoundWordTokenFilter good slow
 * Examples
 *  *   public void testHyphenationCompoundWordsDE() throws Exception {
 *     String[] dict = { "Rind", "Fleisch", "Draht", "Schere", "Gesetz",
 *         "Aufgabe", "Überwachung" };
 * 
 *     Reader reader = new FileReader("de_DR.xml");
 * 
 *     HyphenationTree hyphenator = HyphenationCompoundWordTokenFilter
 *         .getHyphenationTree(reader);
 * 
 *     HyphenationCompoundWordTokenFilter tf = new HyphenationCompoundWordTokenFilter(
 *         new WhitespaceTokenizer(new StringReader(
 *             "Rindfleischüberwachungsgesetz Drahtschere abba")), hyphenator,
 *         dict, CompoundWordTokenFilterBase.DEFAULT_MIN_WORD_SIZE,
 *         CompoundWordTokenFilterBase.DEFAULT_MIN_SUBWORD_SIZE,
 *         CompoundWordTokenFilterBase.DEFAULT_MAX_SUBWORD_SIZE, false);
 *         
 *     CharTermAttribute t = tf.addAttribute(CharTermAttribute.class);
 *     while (tf.incrementToken()) {
 *        System.out.println(t);
 *     }
 *   }
 * 
 *   public void testHyphenationCompoundWordsWithoutDictionaryDE() throws Exception {
 *     Reader reader = new FileReader("de_DR.xml");
 * 
 *     HyphenationTree hyphenator = HyphenationCompoundWordTokenFilter
 *         .getHyphenationTree(reader);
 * 
 *     HyphenationCompoundWordTokenFilter tf = new HyphenationCompoundWordTokenFilter(
 *         new WhitespaceTokenizer(new StringReader(
 *             "Rindfleischüberwachungsgesetz Drahtschere abba")), hyphenator);
 *         
 *     CharTermAttribute t = tf.addAttribute(CharTermAttribute.class);
 *     while (tf.incrementToken()) {
 *        System.out.println(t);
 *     }
 *   }
 *   
 *   public void testDumbCompoundWordsSE() throws Exception {
 *     String[] dict = { "Bil", "Dörr", "Motor", "Tak", "Borr", "Slag", "Hammar",
 *         "Pelar", "Glas", "Ögon", "Fodral", "Bas", "Fiol", "Makare", "Gesäll",
 *         "Sko", "Vind", "Rute", "Torkare", "Blad" };
 * 
 *     DictionaryCompoundWordTokenFilter tf = new DictionaryCompoundWordTokenFilter(
 *         new WhitespaceTokenizer(
 *             new StringReader(
 *                 "Bildörr Bilmotor Biltak Slagborr Hammarborr Pelarborr Glasögonfodral Basfiolsfodral Basfiolsfodralmakaregesäll Skomakare Vindrutetorkare Vindrutetorkarblad abba")),
 *         dict);
 *     CharTermAttribute t = tf.addAttribute(CharTermAttribute.class);
 *     while (tf.incrementToken()) {
 *        System.out.println(t);
 *     }
 *   }
 * 
 */
package org.apache.lucene.analysis.compound;
Token filter	Output quality	Performance
HyphenationCompoundWordTokenFilter	good if grammar file is good – acceptable otherwise	fast
DictionaryCompoundWordTokenFilter	good	slow