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https://issues.apache.org/jira/browse/LUCENE-2230?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Fuad Efendi updated LUCENE-2230:
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Attachment: FuzzyTermEnumNEW.java
FuzzyTermEnumNEW.java
In order to use it with Lucene 2.9.1, complie all files (4 files) in a separate
JAR file (Java 6).
In a source distribution of Lucene 2.9.1, modify FuzzyQuery, single method:
protected FilteredTermEnum getEnum(IndexReader reader) throws IOException {
return new FuzzyTermEnumNEW(reader, getTerm(), minimumSimilarity,
prefixLength);
}
- and complie it (using default settings such as Java 1.4 compatibility); "ant
jar-core" will do it.
Use 2 new jars instead of lucene-core-2.9.1.jar
> Lucene Fuzzy Search: BK-Tree can improve performance 3-20 times.
> ----------------------------------------------------------------
>
> Key: LUCENE-2230
> URL: https://issues.apache.org/jira/browse/LUCENE-2230
> Project: Lucene - Java
> Issue Type: Improvement
> Affects Versions: 3.0
> Environment: Lucene currently uses brute force full-terms scanner and
> calculates distance for each term. New BKTree structure improves performance
> in average 20 times when distance is 1, and 3 times when distance is 3. I
> tested with index size several millions docs, and 250,000 terms.
> New algo uses integer distances between objects.
> Reporter: Fuad Efendi
> Attachments: BKTree.java, Distance.java, DistanceImpl.java,
> FuzzyTermEnumNEW.java
>
> Original Estimate: 0.02h
> Remaining Estimate: 0.02h
>
> W. Burkhard and R. Keller. Some approaches to best-match file searching,
> CACM, 1973
> http://portal.acm.org/citation.cfm?doid=362003.362025
> I was inspired by
> http://blog.notdot.net/2007/4/Damn-Cool-Algorithms-Part-1-BK-Trees (Nick
> Johnson, Google).
> Additionally, simplified algorythm at
> http://www.catalysoft.com/articles/StrikeAMatch.html seems to be much more
> logically correct than Levenstein distance, and it is 3-5 times faster
> (isolated tests).
> Big list od distance implementations:
> http://www.dcs.shef.ac.uk/~sam/stringmetrics.htm
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