Package org.apache.lucene.analysis.compound

A filter that decomposes compound words you find in many Germanic languages into the word parts.


Class Summary
CompoundWordTokenFilterBase Base class for decomposition token filters.
DictionaryCompoundWordTokenFilter A TokenFilter that decomposes compound words found in many Germanic languages.
HyphenationCompoundWordTokenFilter A TokenFilter that decomposes compound words found in many Germanic languages.

Package org.apache.lucene.analysis.compound Description

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
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:

Compound word token filters


The 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: ). The files you need are in the subfolder offo-hyphenation/hyph/ .
Credits for the hyphenation code go to the Apache FOP project .


The 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.


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


  public void testHyphenationCompoundWordsDE() throws Exception {
    String[] dict = { "Rind", "Fleisch", "Draht", "Schere", "Gesetz",
        "Aufgabe", "Überwachung" };

    Reader reader = new FileReader("de_DR.xml");

    HyphenationTree hyphenator = HyphenationCompoundWordTokenFilter

    HyphenationCompoundWordTokenFilter tf = new HyphenationCompoundWordTokenFilter(
        new WhitespaceTokenizer(new StringReader(
            "Rindfleischüberwachungsgesetz Drahtschere abba")), hyphenator,
        dict, CompoundWordTokenFilterBase.DEFAULT_MIN_WORD_SIZE,
        CompoundWordTokenFilterBase.DEFAULT_MAX_SUBWORD_SIZE, false);
    Token t;
    while ((!=null) {
  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")),
    Token t;
    while ((!=null) {

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