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I have a set of documents and I want to identify and remove the outlier documents. I am just wondering if doc2vec can be used for this task.

Or are there any recently evolved, promising algorithms that I can use for this task?

EDIT

I am currently using a bag of words model to identify outliers.

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    $\begingroup$ Is there anything in particular that makes you doubt? What led to this question? $\endgroup$
    – mapto
    Commented Sep 27, 2018 at 13:06

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One way to approach it:

  1. Define a center tendency of the documents, a location in vector space.

  2. Then, define a distance metric (e.g., cosine, Minkowski, or Mahalanobis).

  3. Lastly, set a threshold in the distance metric that would define an outlier.

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