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A filter that decomposes compound words you find in many Germanic
languages to 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 grammer 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. 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);
        
    Token t;
    while ((t=tf.next())!=null) {
       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);
    Token t;
    while ((t=tf.next())!=null) {
       System.out.println(t);
    }
  }