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Learning Document Embeddings by Predicting N-grams for Sentiment
  Classification of Long Movie Reviews

Learning Document Embeddings by Predicting N-grams for Sentiment Classification of Long Movie Reviews

27 December 2015
Bofang Li
Tao Liu
Xiaoyong Du
Deyuan Zhang
Zhe Zhao
ArXivPDFHTML

Papers citing "Learning Document Embeddings by Predicting N-grams for Sentiment Classification of Long Movie Reviews"

4 / 4 papers shown
Title
The Document Vectors Using Cosine Similarity Revisited
The Document Vectors Using Cosine Similarity Revisited
Bingyu Zhang
N. Arefyev
32
9
0
26 May 2022
Explicit Interaction Network for Aspect Sentiment Triplet Extraction
Explicit Interaction Network for Aspect Sentiment Triplet Extraction
Peiyi Wang
Tianyu Liu
Damai Dai
Runxin Xu
Baobao Chang
Zhifang Sui
25
4
0
21 Jun 2021
Using the Tsetlin Machine to Learn Human-Interpretable Rules for
  High-Accuracy Text Categorization with Medical Applications
Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications
G. T. Berge
Ole-Christoffer Granmo
Tor Tveit
Morten Goodwin
Lei Jiao
B. Matheussen
VLM
33
75
0
12 Sep 2018
Modeling Documents with Deep Boltzmann Machines
Modeling Documents with Deep Boltzmann Machines
Nitish Srivastava
Ruslan Salakhutdinov
Geoffrey E. Hinton
BDL
88
184
0
26 Sep 2013
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