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https://issues.apache.org/jira/browse/LUCENE-3921?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13239195#comment-13239195
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Christian Moen commented on LUCENE-3921:
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I've been experimenting with the idea outlined above and I thought I should
share some very early results.
The improvement here is basically to give the compound splitting heuristic an
improved ability to split unknown words that are part of compounds.
Experiments I've run using using our compound splitting test cases suggest that
the effect is indeed positive. The improved heuristic is able to handle some
of the test case that we couldn't do earlier, but all of this requires further
experimentation and validation.
I've been able to segment トートバッグ (tote bag with トート being unknown) and also
ショルダーバッグ (shoulder bag) as you would like with some weight tweaks, but then it
also segmented エンジニアリング (engineering) into エンジニア (engineer) リング (ring).
It might be possible to tune this up or developer a more advanced heuristic
that remedies this, but I haven't had a chance to look further into this.
Also, any change here would require extensive testing and validation. See the
evaluation attached to LUCENE-3726 that was done on Wikipedia for search mode.
Please note that there will not be time to provide improvements here for 3.6,
but we can follow up on katakana segmentation for 4.0.
With the above idea for katakana in mind, I'm thinking we can skip emitting
katakana words that start with ン、ッ、ー since we don't want tokens that start with
these characters and consider adding this as an option to the tokenizer if it
works well.
Having said this, there are real limits to what we can achieve by hacking the
statistical model (and it also affects our karma, you know...). The approach
above also has performance and memory impact. We'd need to introduce a fairly
short limits to how long unknown words can be and this can perhaps only apply
to unknown katakana words. The length restriction will be big enough to not
have any practical impact on segmentation, though.
An alternative approach to all of this is to build some lexical assets. I
think we'd get pretty far for katakana if we apply some of the corpus-based
compound-splitting algorithms Europeans NLP researchers have developed. These
algorithms are simple and quite effective.
Thoughts?
> Add decompose compound Japanese Katakana token capability to Kuromoji
> ---------------------------------------------------------------------
>
> Key: LUCENE-3921
> URL: https://issues.apache.org/jira/browse/LUCENE-3921
> Project: Lucene - Java
> Issue Type: Improvement
> Components: modules/analysis
> Affects Versions: 4.0
> Environment: Cent OS 5, IPA Dictionary, Run with "Search mdoe"
> Reporter: Kazuaki Hiraga
> Labels: features
>
> Japanese morphological analyzer, Kuromoji doesn't have a capability to
> decompose every Japanese Katakana compound tokens to sub-tokens. It seems
> that some Katakana tokens can be decomposed, but it cannot be applied every
> Katakana compound tokens. For instance, "トートバッグ(tote bag)" and "ショルダーバッグ"
> don't decompose into "トート バッグ" and "ショルダー バッグ" although the IPA dictionary
> has "バッグ" in its entry. I would like to apply the decompose feature to every
> Katakana tokens if the sub-tokens are in the dictionary or add the capability
> to force apply the decompose feature to every Katakana tokens.
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