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Posted to dev@tika.apache.org by "Ken Krugler (JIRA)" <ji...@apache.org> on 2010/11/20 22:48:28 UTC
[jira] Updated: (TIKA-369) Improve accuracy of language detection
[ https://issues.apache.org/jira/browse/TIKA-369?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Ken Krugler updated TIKA-369:
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Attachment: textcat.pdf
Including original paper for reference.
> Improve accuracy of language detection
> --------------------------------------
>
> Key: TIKA-369
> URL: https://issues.apache.org/jira/browse/TIKA-369
> Project: Tika
> Issue Type: Improvement
> Components: languageidentifier
> Affects Versions: 0.6
> Reporter: Ken Krugler
> Assignee: Ken Krugler
> Attachments: lingdet-mccs.pdf, Surprise and Coincidence.pdf, textcat.pdf
>
>
> Currently the LanguageProfile code uses 3-grams to find the best language profile using Pearson's chi-square test. This has three issues:
> 1. The results aren't very good for short runs of text. Ted Dunning's paper (attached) indicates that a log-likelihood ratio (LLR) test works much better, which would then make language detection faster due to less text needing to be processed.
> 2. The current LanguageIdentifier.isReasonablyCertain() method uses an exact value as a threshold for certainty. This is very sensitive to the amount of text being processed, and thus gives false negative results for short runs of text.
> 3. Certainty should also be based on how much better the result is for language X, compared to the next best language. If two languages both had identical sum-of-squares values, and this value was below the threshold, then the result is still not very certain.
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