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Recursive neural network
A recursive neural network (RNN) is a kind of deep neural network created by applying the same set of weights recursively over a structure, to…
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Related topics
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12 relations
Broader (1)
Artificial intelligence
Artificial neural network
Backpropagation through structure
Backpropagation through time
Deep learning
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Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2018
Highly Cited
2018
Rumor Detection on Twitter with Tree-structured Recursive Neural Networks
Jing Ma
,
Wei Gao
,
Kam-Fai Wong
Annual Meeting of the Association for…
2018
Corpus ID: 51878172
Automatic rumor detection is technically very challenging. In this work, we try to learn discriminative features from tweets…
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Highly Cited
2018
Highly Cited
2018
Combining Convolutional Neural Network With Recursive Neural Network for Blood Cell Image Classification
G. Liang
,
Huichao Hong
,
Weifang Xie
,
Lixin Zheng
IEEE Access
2018
Corpus ID: 49870021
The diagnosis of blood-related diseases involves the identification and characterization of a patient’s blood sample. As such…
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Highly Cited
2016
Highly Cited
2016
Recursive Neural Conditional Random Fields for Aspect-based Sentiment Analysis
Wenya Wang
,
Sinno Jialin Pan
,
Daniel Dahlmeier
,
Xiaokui Xiao
Conference on Empirical Methods in Natural…
2016
Corpus ID: 11805625
In aspect-based sentiment analysis, extracting aspect terms along with the opinions being expressed from user-generated content…
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Highly Cited
2014
Highly Cited
2014
Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification
Li Dong
,
Furu Wei
,
Chuanqi Tan
,
Duyu Tang
,
M. Zhou
,
Ke Xu
Annual Meeting of the Association for…
2014
Corpus ID: 3158440
We propose Adaptive Recursive Neural Network (AdaRNN) for target-dependent Twitter sentiment classification. AdaRNN adaptively…
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Highly Cited
2014
Highly Cited
2014
Political Ideology Detection Using Recursive Neural Networks
Mohit Iyyer
,
P. Enns
,
Jordan L. Boyd-Graber
,
P. Resnik
Annual Meeting of the Association for…
2014
Corpus ID: 216636598
An individual’s words often reveal their political ideology. Existing automated techniques to identify ideology from text focus…
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Highly Cited
2014
Highly Cited
2014
Deep Recursive Neural Networks for Compositionality in Language
Ozan Irsoy
,
Claire Cardie
Neural Information Processing Systems
2014
Corpus ID: 9792203
Recursive neural networks comprise a class of architecture that can operate on structured input. They have been previously…
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Highly Cited
2013
Highly Cited
2013
Better Word Representations with Recursive Neural Networks for Morphology
Thang Luong
,
R. Socher
,
Christopher D. Manning
Conference on Computational Natural Language…
2013
Corpus ID: 14276764
Vector-space word representations have been very successful in recent years at improving performance across a variety of NLP…
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Review
2012
Review
2012
Semantic Compositionality through Recursive Matrix-Vector Spaces
R. Socher
,
Brody Huval
,
Christopher D. Manning
,
A. Ng
Conference on Empirical Methods in Natural…
2012
Corpus ID: 806709
Single-word vector space models have been very successful at learning lexical information. However, they cannot capture the…
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Highly Cited
2011
Highly Cited
2011
Parsing Natural Scenes and Natural Language with Recursive Neural Networks
R. Socher
,
Cliff Chiung-Yu Lin
,
A. Ng
,
Christopher D. Manning
International Conference on Machine Learning
2011
Corpus ID: 18690358
Recursive structure is commonly found in the inputs of different modalities such as natural scene images or natural language…
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Highly Cited
2010
Highly Cited
2010
Learning Continuous Phrase Representations and Syntactic Parsing with Recursive Neural Networks
R. Socher
,
Christopher D. Manning
,
A. Ng
2010
Corpus ID: 9923502
Natural language parsing has typically been done with small sets of discrete categories such as NP and VP, but this…
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