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improve fuzzyquery javadocs 

git-svn-id: https://svn.apache.org/repos/asf/lucene/dev/trunk@1384473 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Robert Muir 2012-09-13 19:02:24 +00:00
parent d6570e8a41
commit e905312abc
1 changed files with 10 additions and 1 deletions
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11
lucene/core/src/java/org/apache/lucene/search/FuzzyQuery.java
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@ -28,12 +28,21 @@ import org.apache.lucene.util.ToStringUtils;
import org.apache.lucene.util.automaton.LevenshteinAutomata;
/** Implements the fuzzy search query. The similarity measurement
* is based on the Damerau-Levenshtein (optimal string alignment) algorithm.
* is based on the Damerau-Levenshtein (optimal string alignment) algorithm,
* though you can explicitly choose classic Levenshtein by passing <code>false</code>
* to the <code>transpositions</code> parameter.
*
* <p>This query uses {@link MultiTermQuery.TopTermsScoringBooleanQueryRewrite}
* as default. So terms will be collected and scored according to their
* edit distance. Only the top terms are used for building the {@link BooleanQuery}.
* It is not recommended to change the rewrite mode for fuzzy queries.
*
* <p>At most, this query will match terms up to
* {@value org.apache.lucene.util.automaton.LevenshteinAutomata#MAXIMUM_SUPPORTED_DISTANCE} edits.
* Higher distances (especially with transpositions enabled), are generally not useful and
* will match a significant amount of the term dictionary. If you really want this, consider
* using an n-gram indexing technique (such as the SpellChecker in the
* <a href="{@docRoot}/../suggest/overview-summary.html">suggest module</a>) instead.
*/
public class FuzzyQuery extends MultiTermQuery {