[jira] [Commented] (TIKA-1443) Add a junk text detector to Tika

["Tim Allison (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/TIKA-1443?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14982597#comment-14982597 ] 

Tim Allison commented on TIKA-1443:
-----------------------------------

[~kkrugler], have you looked at how Optimaize has worked on garbled text, by chance?  With the default settings and models in lang-detect, we're getting very high confidence for 'bn' (for example) for entirely garbled text.  Short of using a common word lookup list (see [discussion|https://issues.apache.org/jira/browse/PDFBOX-3058?focusedCommentId=14981928&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-14981928]), I'd hope that uni/bi/trigram character models would offer some insight into whether something went horribly wrong during text extraction.

> Add a junk text detector to Tika
> --------------------------------
>
>                 Key: TIKA-1443
>                 URL: https://issues.apache.org/jira/browse/TIKA-1443
>             Project: Tika
>          Issue Type: Wish
>            Reporter: Tim Allison
>            Priority: Minor
>
> It would be helpful to have a detector that flags documents whose extracted text is junk.  This could be used as a component of TIKA-1332 or as a standalone detector.  See TIKA-1332 for some initial ideas of what statistics we might use for such a detector.
> Two use cases:
> * Parser developers could quickly see whether changes in code lead to less "junky" documents or more "junky" documents.  This would also aid in prioritizing manual review of output comparison (see discussion in TIKA-1419).
> * Search system integrators could use that information to set document specific relevancy rankings or to avoid indexing a document



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