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From "Peter Mountanos (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-14864) [MLLIB] Implement Doc2Vec
Date Mon, 02 May 2016 00:46:12 GMT

    [ https://issues.apache.org/jira/browse/SPARK-14864?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15266024#comment-15266024
] 

Peter Mountanos commented on SPARK-14864:
-----------------------------------------

I will try to work out this issue if no one else has made any progress.

> [MLLIB] Implement Doc2Vec
> -------------------------
>
>                 Key: SPARK-14864
>                 URL: https://issues.apache.org/jira/browse/SPARK-14864
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>            Reporter: Peter Mountanos
>            Priority: Minor
>
> It would be useful to implement Doc2Vec, as described in the paper [Distributed Representations
of Sentences and Documents|https://cs.stanford.edu/~quocle/paragraph_vector.pdf]. Gensim has
an implementation [Deep learning with paragraph2vec|https://radimrehurek.com/gensim/models/doc2vec.html].

> Le & Mikolov show that when aggregating Word2Vec vector representations for a paragraph/document,
it does not perform well for prediction tasks. Instead, they propose the Paragraph Vector
implementation, which provides state-of-the-art results on several text classification and
sentiment analysis tasks.



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