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https://issues.apache.org/jira/browse/LUCENE-6747?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Mark Harwood updated LUCENE-6747:
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Attachment: fingerprintv2.patch
Thanks for taking a look, Adrien.
Added a v2 patch with following changes:
1) added call to input.end() to get final offset state
2) final state is retained using captureState()
3) Added a FingerprintFilterFactory class
As for the alternative hashing idea :
For speed reasons this would be a nice idea but reduces the read-ability of
results if you want to debug any collisions or otherwise display connections.
For compactness reasons (storing in doc values etc) it would always be possible
to chain a conventional hashing algo in a TokenFilter on the end of this
text-normalizing filter. (Do we already have a conventional hashing
TokenFilter?)
> FingerprintFilter - a TokenFilter for clustering/linking purposes
> -----------------------------------------------------------------
>
> Key: LUCENE-6747
> URL: https://issues.apache.org/jira/browse/LUCENE-6747
> Project: Lucene - Core
> Issue Type: New Feature
> Components: modules/analysis
> Reporter: Mark Harwood
> Priority: Minor
> Attachments: fingerprintv1.patch, fingerprintv2.patch
>
>
> A TokenFilter that emits a single token which is a sorted, de-duplicated set
> of the input tokens.
> This approach to normalizing text is used in tools like OpenRefine[1] and
> elsewhere [2] to help in clustering or linking texts.
> The implementation proposed here has a an upper limit on the size of the
> combined token which is output.
> [1] https://github.com/OpenRefine/OpenRefine/wiki/Clustering-In-Depth
> [2]
> https://rajmak.wordpress.com/2013/04/27/clustering-text-map-reduce-in-python/
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