Which approach/algorithm for supervised topic modeling of a large corpus of short online comments?
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I have a corpus of about 1M documents (short comments from a crowdsourcing website); about 5k documents have been manually labeled, each with one of ~20 topics (training data).
What topic modeling approach I should use to train a model that can label the rest of the documents?
supervised-learning topic-model
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$begingroup$
I have a corpus of about 1M documents (short comments from a crowdsourcing website); about 5k documents have been manually labeled, each with one of ~20 topics (training data).
What topic modeling approach I should use to train a model that can label the rest of the documents?
supervised-learning topic-model
New contributor
$endgroup$
add a comment |
$begingroup$
I have a corpus of about 1M documents (short comments from a crowdsourcing website); about 5k documents have been manually labeled, each with one of ~20 topics (training data).
What topic modeling approach I should use to train a model that can label the rest of the documents?
supervised-learning topic-model
New contributor
$endgroup$
I have a corpus of about 1M documents (short comments from a crowdsourcing website); about 5k documents have been manually labeled, each with one of ~20 topics (training data).
What topic modeling approach I should use to train a model that can label the rest of the documents?
supervised-learning topic-model
supervised-learning topic-model
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New contributor
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asked 2 mins ago
Dr. KaufmanDr. Kaufman
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Dr. Kaufman is a new contributor. Be nice, and check out our Code of Conduct.
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