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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. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org