2017-12-01 · article · Topic Modeling · en
highly citedClaims drawn from cited facts, not live model generation.
This paper is an article, so it is a formal publication whose findings should be given the weight of peer-reviewed research. Its primary topic is topic modeling, and its title identifies it as a focused contribution within that area rather than a preprint.
3 cited facts
A small team of 3 researchers authored this work.
1 cited fact
With 9,880 citations, this work has already become an established reference point in its field, far surpassing the threshold for outsized influence. Its 47 references anchor a compact scholarly foundation, suggesting a focused rather than exhaustive literature review.
3 cited facts
Enriching Word Vectors with Subword Information is an article, focusing on Topic Modeling, published in 2017.
Enriching Word Vectors with Subword Information has 9,880 citations in our record, placing it among the highly cited works we track.
Our record lists 3 authors for Enriching Word Vectors with Subword Information and references 47 other works. Author names aren't in our data yet — the source link on the page lists the full byline.
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