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From "Brooke Schreier Ganz (Commented) (JIRA)" <>
Subject [jira] [Commented] (SOLR-2982) Upgrade Apache Commons Codec to version 1.6 in order to add new Beider-Morse Phonetic Matching (BMPM) option
Date Fri, 30 Dec 2011 05:17:30 GMT


Brooke Schreier Ganz commented on SOLR-2982:

Thank you so much for working on this!  I just tested out the latest nightly build on my laptop
and everything works great.

I use Solr to run a non-profit group's 190,000+ record genealogy database and this new ability
to do proper soundalike surname searches through our listings of consonant-heavy Central and
Eastern European surnames (and their multitudes of "creative" spelling variants) will make
things *a lot* easier.  You just made a lot of genealogists very happy.  :-)

Thanks again!
> Upgrade Apache Commons Codec to version 1.6 in order to add new Beider-Morse Phonetic
Matching (BMPM) option
> ------------------------------------------------------------------------------------------------------------
>                 Key: SOLR-2982
>                 URL:
>             Project: Solr
>          Issue Type: Improvement
>          Components: Rules, Schema and Analysis, search
>            Reporter: Brooke Schreier Ganz
>              Labels: codec, commons, commons-codec, language, names, phonetic, search,
searching, soundalike
>             Fix For: 3.6, 4.0
>         Attachments: SOLR-2982.patch
> Apache Commons Codec released version 1.6 of their codec pack in November, 2011.  Along
with a few bug fixes, 1.6 contains a great new phonetic matching system called Beider-Morse
Phonetic Matching (BMPM) that is far superior to the existing phonetic codecs, such as regular
soundex, metaphone, caverphone, and so on.  BMPM has actually been available for some time,
but this is the first port of it to java, and its first commit in the Apache ecosystem.
> For a lot more information, see here:   and
> BMPM would be a fantastic "soundalike" tool to help search for personal names (or just
surnames) in a Solr/Lucene index, much better than Levenshtein distance for this use case.

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