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https://issues.apache.org/jira/browse/LUCENE-1629?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12710147#action_12710147
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Mingfai Ma commented on LUCENE-1629:
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i'm not sure if the character mapping is a feasible approach. The CC-CEDICT
dictionary has terms in both simplified and traditional chinese already and we
need not to define any rule. how much effort is needed to define all mapping
rules for the simplified and traditional chinese thesaurus?
Besides, simplified and traditional Chinese conversion is not as simple as
mapping the code. For the sample meaning, it may use different words in the SC
and TC.
if the approach accepted in this issue is ok, I just need to figure out how to
convert CC-CEDICT to the dct / mem format, and i suppose it is doable.
> contrib intelligent Analyzer for Chinese
> ----------------------------------------
>
> Key: LUCENE-1629
> URL: https://issues.apache.org/jira/browse/LUCENE-1629
> Project: Lucene - Java
> Issue Type: Improvement
> Components: contrib/analyzers
> Affects Versions: 2.4.1
> Environment: for java 1.5 or higher, lucene 2.4.1
> Reporter: Xiaoping Gao
> Assignee: Michael McCandless
> Fix For: 2.9
>
> Attachments: analysis-data.zip, bigramdict.mem,
> build-resources-with-folder.patch, build-resources.patch,
> build-resources.patch, coredict.mem, LUCENE-1629-encoding-fix.patch,
> LUCENE-1629-java1.4.patch
>
>
> I wrote a Analyzer for apache lucene for analyzing sentences in Chinese
> language. it's called "imdict-chinese-analyzer", the project on google code
> is here: http://code.google.com/p/imdict-chinese-analyzer/
> In Chinese, "我是中国人"(I am Chinese), should be tokenized as "我"(I) "是"(am)
> "中国人"(Chinese), not "我" "是中" "国人". So the analyzer must handle each sentence
> properly, or there will be mis-understandings everywhere in the index
> constructed by Lucene, and the accuracy of the search engine will be affected
> seriously!
> Although there are two analyzer packages in apache repository which can
> handle Chinese: ChineseAnalyzer and CJKAnalyzer, they take each character or
> every two adjoining characters as a single word, this is obviously not true
> in reality, also this strategy will increase the index size and hurt the
> performance baddly.
> The algorithm of imdict-chinese-analyzer is based on Hidden Markov Model
> (HMM), so it can tokenize chinese sentence in a really intelligent way.
> Tokenizaion accuracy of this model is above 90% according to the paper
> "HHMM-based Chinese Lexical analyzer ICTCLAL" while other analyzer's is about
> 60%.
> As imdict-chinese-analyzer is a really fast and intelligent. I want to
> contribute it to the apache lucene repository.
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