YNU-HPCC at SemEval-2019 Task 9: Using a BERT and CNN-BiLSTM-GRU Model for Suggestion Mining

Consumer opinions towards commercial entities are generally expressed through online reviews, blogs, and discussion forums. These opinions largely express positive and negative sentiments towards a given entity,but also tend to contain suggestions for improving the entity. In this task, we extract suggestions from given the unstructured text, compared to the traditional opinion mining systems. Such suggestion mining is more applicability and extends capabilities.

[1]  Nitish Srivastava,et al.  Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.

[2]  Tianshi Li,et al.  Semantic Role Labeling Using Recursive Neural Network , 2015, CCL.

[3]  Paul Buitelaar,et al.  SemEval-2019 Task 9: Suggestion Mining from Online Reviews and Forums , 2019, *SEMEVAL.

[4]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[5]  Lawrence D. Jackel,et al.  Handwritten Digit Recognition with a Back-Propagation Network , 1989, NIPS.

[6]  Ming-Wei Chang,et al.  BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.

[7]  Alex Graves,et al.  Long Short-Term Memory , 2020, Computer Vision.

[8]  Mohsen Rashwan,et al.  Word Representations in Vector Space and their Applications for Arabic , 2015, CICLing.

[9]  Björn W. Schuller,et al.  Social signal classification using deep blstm recurrent neural networks , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[10]  George Kurian,et al.  Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation , 2016, ArXiv.

[11]  Geoffrey E. Hinton,et al.  Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.

[12]  Yoshua Bengio,et al.  Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.

[13]  Hsin-Hsi Chen,et al.  Less is More: Filtering Abnormal Dimensions in GloVe , 2016, WWW.

[14]  Jürgen Schmidhuber,et al.  LSTM: A Search Space Odyssey , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[15]  Kaiming He,et al.  Focal Loss for Dense Object Detection , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).