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https://issues.apache.org/jira/browse/LUCENE-6837?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15010673#comment-15010673
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Christian Moen commented on LUCENE-6837:
----------------------------------------

Tokenizing Japanese Wikipedia seems fine with nBestCost set, but it seems like 
random-blasting doesn't pass.

Konno-san, I'm wondering if I can ask you the trouble of looking into why the 
{{testRandomHugeStrings}} fails with the latest patch?

The test basically does random-blasting with nBestCost set to 2000.  I think 
it's a good idea that we fix this before we commit.  I believe it's easily 
reproducible, but I used

{noformat}
ant test  -Dtestcase=TestJapaneseTokenizer -Dtests.method=testRandomHugeStrings 
-Dtests.seed=99EB179B92E66345 -Dtests.slow=true -Dtests.locale=sr_CS 
-Dtests.timezone=PNT -Dtests.asserts=true -Dtests.file.encoding=US-ASCII
{noformat}

in my environment.

> Add N-best output capability to JapaneseTokenizer
> -------------------------------------------------
>
>                 Key: LUCENE-6837
>                 URL: https://issues.apache.org/jira/browse/LUCENE-6837
>             Project: Lucene - Core
>          Issue Type: Improvement
>          Components: modules/analysis
>    Affects Versions: 5.3
>            Reporter: KONNO, Hiroharu
>            Assignee: Christian Moen
>            Priority: Minor
>         Attachments: LUCENE-6837.patch, LUCENE-6837.patch, LUCENE-6837.patch
>
>
> Japanese morphological analyzers often generate mis-segmented tokens. N-best 
> output reduces the impact of mis-segmentation on search result. N-best output 
> is more meaningful than character N-gram, and it increases hit count too.
> If you use N-best output, you can get decompounded tokens (ex: 
> "シニアソフトウェアエンジニア" => {"シニア", "シニアソフトウェアエンジニア", "ソフトウェア", "エンジニア"}) and 
> overwrapped tokens (ex: "数学部長谷川" => {"数学", "部", "部長", "長谷川", "谷川"}), 
> depending on the dictionary and N-best parameter settings.



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