| /* |
| * 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: |
| * <table border="1" summary="example input stream"> |
| * <tr> |
| * <th>Input token stream</th> |
| * </tr> |
| * <tr> |
| * <td>Rindfleischüberwachungsgesetz Drahtschere abba</td> |
| * </tr> |
| * </table> |
| * <br> |
| * <table border="1" summary="example output stream"> |
| * <tr> |
| * <th>Output token stream</th> |
| * </tr> |
| * <tr> |
| * <td>(Rindfleischüberwachungsgesetz,0,29)</td> |
| * </tr> |
| * <tr> |
| * <td>(Rind,0,4,posIncr=0)</td> |
| * </tr> |
| * <tr> |
| * <td>(fleisch,4,11,posIncr=0)</td> |
| * </tr> |
| * <tr> |
| * <td>(überwachung,11,22,posIncr=0)</td> |
| * </tr> |
| * <tr> |
| * <td>(gesetz,23,29,posIncr=0)</td> |
| * </tr> |
| * <tr> |
| * <td>(Drahtschere,30,41)</td> |
| * </tr> |
| * <tr> |
| * <td>(Draht,30,35,posIncr=0)</td> |
| * </tr> |
| * <tr> |
| * <td>(schere,35,41,posIncr=0)</td> |
| * </tr> |
| * <tr> |
| * <td>(abba,42,46)</td> |
| * </tr> |
| * </table> |
| * |
| * 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: |
| * <ul> |
| * <li><i>HyphenationCompoundWordTokenFilter</i>: it uses a |
| * hyphenation grammar based approach to find potential word parts of a |
| * given word.</li> |
| * <li><i>DictionaryCompoundWordTokenFilter</i>: it uses a |
| * brute-force dictionary-only based approach to find the word parts of a given |
| * word.</li> |
| * </ul> |
| * |
| * <h3>Compound word token filters</h3> |
| * <h4>HyphenationCompoundWordTokenFilter</h4> |
| * 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. |
| * <h5>Grammar file</h5> |
| * 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 |
| * <a href="http://offo.sourceforge.net/hyphenation/index.html">Objects |
| * For Formatting Objects</a> |
| * (OFFO) Sourceforge project (direct link to download the pattern files: |
| * <a href="http://downloads.sourceforge.net/offo/offo-hyphenation.zip">http://downloads.sourceforge.net/offo/offo-hyphenation.zip</a> |
| * ). The files you need are in the subfolder |
| * <i>offo-hyphenation/hyph/</i> |
| * . |
| * <br> |
| * Credits for the hyphenation code go to the |
| * <a href="http://xmlgraphics.apache.org/fop/">Apache FOP project</a> |
| * . |
| * |
| * <h4>DictionaryCompoundWordTokenFilter</h4> |
| * 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. |
| * |
| * <h3>Dictionary</h3> |
| * 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 |
| * <a href="http://wiki.services.openoffice.org/wiki/Dictionaries">OpenOffice |
| * dictionaries</a> |
| * Wiki. |
| * |
| * <h3>Which variant should I use?</h3> |
| * This decision matrix should help you: |
| * <table border="1" summary="comparison of dictionary and hyphenation based decompounding"> |
| * <tr> |
| * <th>Token filter</th> |
| * <th>Output quality</th> |
| * <th>Performance</th> |
| * </tr> |
| * <tr> |
| * <td>HyphenationCompoundWordTokenFilter</td> |
| * <td>good if grammar file is good – acceptable otherwise</td> |
| * <td>fast</td> |
| * </tr> |
| * <tr> |
| * <td>DictionaryCompoundWordTokenFilter</td> |
| * <td>good</td> |
| * <td>slow</td> |
| * </tr> |
| * </table> |
| * <h3>Examples</h3> |
| * <pre class="prettyprint"> |
| * 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); |
| * } |
| * } |
| * </pre> |
| */ |
| package org.apache.lucene.analysis.compound; |
