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Doc2Vec on the PubMed corpus: study of a new approach to generate
  related articles

Doc2Vec on the PubMed corpus: study of a new approach to generate related articles

26 November 2019
Emeric Dynomant
Stéfan J. Darmoni
Émeline Lejeune
G. Kerdelhué
J. Leroy
Vincent Lequertier
S. Canu
Julien Grosjean
ArXivPDFHTML

Papers citing "Doc2Vec on the PubMed corpus: study of a new approach to generate related articles"

5 / 5 papers shown
Title
BioSentVec: creating sentence embeddings for biomedical texts
BioSentVec: creating sentence embeddings for biomedical texts
Qingyu Chen
Yifan Peng
Zhiyong Lu
62
214
0
22 Oct 2018
Unsupervised Learning of Sentence Embeddings using Compositional n-Gram
  Features
Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Features
Matteo Pagliardini
Prakhar Gupta
Martin Jaggi
SSL
143
694
0
07 Mar 2017
An Empirical Evaluation of doc2vec with Practical Insights into Document
  Embedding Generation
An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation
Jey Han Lau
Timothy Baldwin
127
652
0
19 Jul 2016
Distributed Representations of Sentences and Documents
Distributed Representations of Sentences and Documents
Quoc V. Le
Tomas Mikolov
FaML
249
9,239
0
16 May 2014
Distributed Representations of Words and Phrases and their
  Compositionality
Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov
Ilya Sutskever
Kai Chen
G. Corrado
J. Dean
NAI
OCL
371
33,520
0
16 Oct 2013
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