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From "Robert Muir (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (TIKA-369) Improve accuracy of language detection
Date Thu, 07 Feb 2013 18:27:14 GMT

    [ https://issues.apache.org/jira/browse/TIKA-369?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13573753#comment-13573753
] 

Robert Muir commented on TIKA-369:
----------------------------------

The DetectorFactory is definitely gnarly, but you can load the JSON of the profiles 
yourself from resource files e.g. in the JAR and use loadProfile(List<String> json_profiles).


This is how solr worked around the issue of wanting to bundle profiles easily in the JAR.

                
> 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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