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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (TIKA-2016) A parser that combines Apache OpenNLP and Apache Tika and provides facilities for automatically deriving sentiment from text.
Date Tue, 02 May 2017 03:52:04 GMT

    [ https://issues.apache.org/jira/browse/TIKA-2016?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15992294#comment-15992294
] 

ASF GitHub Bot commented on TIKA-2016:
--------------------------------------

thammegowda commented on issue #169: TIKA-2016  Sentiment Analysis Parser Contributed by amensiko
and thammegowda
URL: https://github.com/apache/tika/pull/169#issuecomment-298491221
 
 
   I thought no further action needed on this PR (looks like I missed something, sorry!)
   
   If it is about the categorical analysis, there are no code changes needed.
   
   Just use this config for `--config=` argument above.
   ```xml
   <properties>
       <parsers>
           <parser class="org.apache.tika.parser.sentiment.analysis.SentimentParser">
               <mime>text/plain</mime>
               <mime>application/sentiment</mime>
               <params>
                   <!--This is default <param name="modelPath" type="string">https://raw.githubusercontent.com/USCDataScience/SentimentAnalysisParser/master/sentiment-models/en-netflix-sentiment.bin</param>
-->
                   <param name="modelPath" type="string">https://raw.githubusercontent.com/USCDataScience/SentimentAnalysisParser/master/sentiment-models/ht-sentiment-categ.bin</param>
                   <!--This can also be relative path sentiment-models/en-stanford-sentiment.bin-->
               </params>
           </parser>
       </parsers>
   </properties>
   ```
   I tested again now, it worked!
   - Users are free to point to any opennlp classifier model they wish to. 
   - The `modelPath` can be HTTP URL or local file path or relative path to the classloader.
   
   I thought I handled all the cases with our awesome XML parameter binding feature.
   
    What did I miss? 
 
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> A parser that combines Apache OpenNLP and Apache Tika and provides facilities for automatically
deriving sentiment from text.
> -----------------------------------------------------------------------------------------------------------------------------
>
>                 Key: TIKA-2016
>                 URL: https://issues.apache.org/jira/browse/TIKA-2016
>             Project: Tika
>          Issue Type: New Feature
>          Components: parser
>            Reporter: Anastasija Mensikova
>            Assignee: Chris A. Mattmann
>              Labels: analysis, gsoc2016, memex, parser, sentiment
>             Fix For: 1.15
>
>
> A new project that implements a parser that uses Apache OpenNLP and Apache Tika to perform
Sentiment Analysis.



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