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  1. Lucene - Core
  2. LUCENE-8231

Nori, a Korean analyzer based on mecab-ko-dic

    Details

    • Type: New Feature
    • Status: Closed
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: None
    • Fix Version/s: 7.4, master (8.0)
    • Component/s: modules/analysis
    • Labels:
      None
    • Lucene Fields:
      New

      Description

      There is a dictionary similar to IPADIC but for Korean called mecab-ko-dic:
      It is available under an Apache license here:
      https://bitbucket.org/eunjeon/mecab-ko-dic

      This dictionary was built with MeCab, it defines a format for the features adapted for the Korean language.
      Since the Kuromoji tokenizer uses the same format for the morphological analysis (left cost + right cost + word cost) I tried to adapt the module to handle Korean with the mecab-ko-dic. I've started with a POC that copies the Kuromoji module and adapts it for the mecab-ko-dic.
      I used the same classes to build and read the dictionary but I had to make some modifications to handle the differences with the IPADIC and Japanese.
      The resulting binary dictionary takes 28MB on disk, it's bigger than the IPADIC but mainly because the source is bigger and there are a lot of
      compound and inflect terms that define a group of terms and the segmentation that can be applied.
      I attached the patch that contains this new Korean module called godori nori. It is an adaptation of the Kuromoji module so currently
      the two modules don't share any code. I wanted to validate the approach first and check the relevancy of the results. I don't speak Korean so I used the relevancy
      tests that was added for another Korean tokenizer (https://issues.apache.org/jira/browse/LUCENE-4956) and tested the output against mecab-ko which is the official fork of mecab to use the mecab-ko-dic.
      I had to simplify the JapaneseTokenizer, my version removes the nBest output and the decomposition of too long tokens. I also
      modified the handling of whitespaces since they are important in Korean. Whitespaces that appear before a term are attached to that term and this
      information is used to compute a penalty based on the Part of Speech of the token. The penalty cost is a feature added to mecab-ko to handle
      morphemes that should not appear after a morpheme and is described in the mecab-ko page:
      https://bitbucket.org/eunjeon/mecab-ko
      Ignoring whitespaces is also more inlined with the official MeCab library which attach the whitespaces to the term that follows.
      I also added a decompounder filter that expand the compounds and inflects defined in the dictionary and a part of speech filter similar to the Japanese
      that removes the morpheme that are not useful for relevance (suffix, prefix, interjection, ...). These filters don't play well with the tokenizer if it can
      output multiple paths (nBest output for instance) so for simplicity I removed this ability and the Korean tokenizer only outputs the best path.
      I compared the result with mecab-ko to confirm that the analyzer is working and ran the relevancy test that is defined in HantecRel.java included
      in the patch (written by Robert for another Korean analyzer). Here are the results:

      Analyzer Index Time Index Size MAP(CLASSIC) MAP(BM25) MAP(GL2)
      Standard 35s 131MB .007 .1044 .1053
      CJK 36s 164MB .1418 .1924 .1916
      Korean 212s 90MB .1628 .2094 .2078

      I find the results very promising so I plan to continue to work on this project. I started to extract the part of the code that could be shared with the
      Kuromoji module but I wanted to share the status and this POC first to confirm that this approach is viable. The advantages of using the same model than
      the Japanese analyzer are multiple: we don't have a Korean analyzer at the moment , the resulting dictionary is small compared to other libraries that
      use the mecab-ko-dic (the FST takes only 5.4MB) and the Tokenizer prunes the lattice on the fly to select the best path efficiently.
      The dictionary can be built directly from the godori module with the following command:
      ant regenerate (you need to create the resource directory (mkdir lucene/analysis/godori/src/resources/org/apache/lucene/analysis/ko/dict) first since the dictionary is not included in the patch).
      I've also added some minimal tests in the module to play with the analysis.

        Attachments

        1. LUCENE-8231.patch
          234 kB
          Jim Ferenczi
        2. LUCENE-8231.patch
          229 kB
          Jim Ferenczi
        3. LUCENE-8231.patch
          229 kB
          Jim Ferenczi
        4. LUCENE-8231.patch
          229 kB
          Jim Ferenczi
        5. LUCENE-8231.patch
          242 kB
          Jim Ferenczi
        6. LUCENE-8231.patch
          240 kB
          Jim Ferenczi
        7. LUCENE-8231.patch
          240 kB
          Jim Ferenczi
        8. LUCENE-8231.patch
          224 kB
          Jim Ferenczi
        9. LUCENE-8231.patch
          219 kB
          Jim Ferenczi
        10. LUCENE-8231.patch
          211 kB
          Jim Ferenczi
        11. LUCENE-8231.patch
          206 kB
          Jim Ferenczi
        12. LUCENE-8231-remap-hangul.patch
          215 kB
          Jim Ferenczi

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              • Assignee:
                Unassigned
                Reporter:
                jim.ferenczi Jim Ferenczi
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                Dates

                • Created:
                  Updated:
                  Resolved: