@inproceedings{rouvier-2017-lia,
title = "{LIA} at {S}em{E}val-2017 Task 4: An Ensemble of Neural Networks for Sentiment Classification",
author = "Rouvier, Mickael",
editor = "Bethard, Steven and
Carpuat, Marine and
Apidianaki, Marianna and
Mohammad, Saif M. and
Cer, Daniel and
Jurgens, David",
booktitle = "Proceedings of the 11th International Workshop on Semantic Evaluation ({S}em{E}val-2017)",
month = aug,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S17-2128",
doi = "10.18653/v1/S17-2128",
pages = "760--765",
abstract = "This paper describes the system developed at LIA for the SemEval-2017 evaluation campaign. The goal of Task 4.A was to identify sentiment polarity in tweets. The system is an ensemble of Deep Neural Network (DNN) models: Convolutional Neural Network (CNN) and Recurrent Neural Network Long Short-Term Memory (RNN-LSTM). We initialize the input representation of DNN with different sets of embeddings trained on large datasets. The ensemble of DNNs are combined using a score-level fusion approach. The system ranked 2nd at SemEval-2017 and obtained an average recall of 67.6{\%}.",
}
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%0 Conference Proceedings
%T LIA at SemEval-2017 Task 4: An Ensemble of Neural Networks for Sentiment Classification
%A Rouvier, Mickael
%Y Bethard, Steven
%Y Carpuat, Marine
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%Y Cer, Daniel
%Y Jurgens, David
%S Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F rouvier-2017-lia
%X This paper describes the system developed at LIA for the SemEval-2017 evaluation campaign. The goal of Task 4.A was to identify sentiment polarity in tweets. The system is an ensemble of Deep Neural Network (DNN) models: Convolutional Neural Network (CNN) and Recurrent Neural Network Long Short-Term Memory (RNN-LSTM). We initialize the input representation of DNN with different sets of embeddings trained on large datasets. The ensemble of DNNs are combined using a score-level fusion approach. The system ranked 2nd at SemEval-2017 and obtained an average recall of 67.6%.
%R 10.18653/v1/S17-2128
%U https://aclanthology.org/S17-2128
%U https://doi.org/10.18653/v1/S17-2128
%P 760-765
Markdown (Informal)
[LIA at SemEval-2017 Task 4: An Ensemble of Neural Networks for Sentiment Classification](https://aclanthology.org/S17-2128) (Rouvier, SemEval 2017)
ACL