DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction

This paper focuses on two related subtasks of aspect-based sentiment analysis, namely aspect term extraction and aspect sentiment classification, which we call aspect term-polarity co-extraction. The former task is to extract aspects of a product or service from an opinion document, and the latter is to identify the polarity expressed in the document about these extracted aspects. Most existing algorithms address them as two separate tasks and solve them one by one, or only perform one task, which can be complicated for real applications. In this paper, we treat these two tasks as two sequence labeling problems and propose a novel Dual crOss-sharEd RNN framework (DOER) to generate all aspect term-polarity pairs of the input sentence simultaneously. Specifically, DOER involves a dual recurrent neural network to extract the respective representation of each task, and a cross-shared unit to consider the relationship between them. Experimental results demonstrate that the proposed framework outperforms state-of-the-art baselines on three benchmark datasets.

[1]  Xu Ling,et al.  Topic sentiment mixture: modeling facets and opinions in weblogs , 2007, WWW '07.

[2]  Benjamin Van Durme,et al.  Open Domain Targeted Sentiment , 2013, EMNLP.

[3]  Richard Socher,et al.  Aspect Specific Sentiment Analysis Using Hierarchical Deep Learning , 2014 .

[4]  Iryna Gurevych,et al.  Extracting Opinion Targets in a Single and Cross-Domain Setting with Conditional Random Fields , 2010, EMNLP.

[5]  Xiang Ren,et al.  Empower Sequence Labeling with Task-Aware Neural Language Model , 2017, AAAI.

[6]  Tao Li,et al.  Aspect Based Sentiment Analysis with Gated Convolutional Networks , 2018, ACL.

[7]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[8]  Xiaocheng Feng,et al.  Effective LSTMs for Target-Dependent Sentiment Classification , 2015, COLING.

[9]  Houfeng Wang,et al.  Interactive Attention Networks for Aspect-Level Sentiment Classification , 2017, IJCAI.

[10]  Jürgen Schmidhuber,et al.  Framewise phoneme classification with bidirectional LSTM and other neural network architectures , 2005, Neural Networks.

[11]  Chun Chen,et al.  Opinion Word Expansion and Target Extraction through Double Propagation , 2011, CL.

[12]  Eduard H. Hovy,et al.  End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF , 2016, ACL.

[13]  Jeffrey Pennington,et al.  GloVe: Global Vectors for Word Representation , 2014, EMNLP.

[14]  Xiaokui Xiao,et al.  Recursive Neural Conditional Random Fields for Aspect-based Sentiment Analysis , 2016, EMNLP.

[15]  Arjun Mukherjee,et al.  Extracting Aspect Specific Opinion Expressions , 2016, EMNLP.

[16]  Suresh Manandhar,et al.  SemEval-2014 Task 4: Aspect Based Sentiment Analysis , 2014, *SEMEVAL.

[17]  Christopher Potts,et al.  Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank , 2013, EMNLP.

[18]  Xin Li,et al.  A Unified Model for Opinion Target Extraction and Target Sentiment Prediction , 2018, AAAI.

[19]  Joachim Wagner,et al.  DCU: Aspect-based Polarity Classification for SemEval Task 4 , 2014, *SEMEVAL.

[20]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[21]  Erik Cambria,et al.  Aspect extraction for opinion mining with a deep convolutional neural network , 2016, Knowl. Based Syst..

[22]  Bing Liu,et al.  Mining and summarizing customer reviews , 2004, KDD.

[23]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[24]  Nitish Srivastava,et al.  Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..

[25]  Shuai Wang,et al.  Target-Sensitive Memory Networks for Aspect Sentiment Classification , 2018, ACL.

[26]  Siu Cheung Hui,et al.  Learning to Attend via Word-Aspect Associative Fusion for Aspect-based Sentiment Analysis , 2017, AAAI.

[27]  Wei Lu,et al.  Learning Latent Sentiment Scopes for Entity-Level Sentiment Analysis , 2017, AAAI.

[28]  Guillaume Lample,et al.  Neural Architectures for Named Entity Recognition , 2016, NAACL.

[29]  Yue Zhang,et al.  Neural Networks for Open Domain Targeted Sentiment , 2015, EMNLP.

[30]  Philip S. Yu,et al.  Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction , 2018, ACL.

[31]  Jeffrey Dean,et al.  Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.

[32]  Li Zhao,et al.  Attention-based LSTM for Aspect-level Sentiment Classification , 2016, EMNLP.

[33]  Iryna Gurevych,et al.  Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging , 2017, EMNLP.

[34]  Haris Papageorgiou,et al.  SemEval-2016 Task 5: Aspect Based Sentiment Analysis , 2016, *SEMEVAL.

[35]  Wei Lu,et al.  Learning Latent Opinions for Aspect-level Sentiment Classification , 2018, AAAI.

[36]  Ming Zhou,et al.  Unsupervised Word and Dependency Path Embeddings for Aspect Term Extraction , 2016, IJCAI.

[37]  Tiejun Zhao,et al.  Target-dependent Twitter Sentiment Classification , 2011, ACL.

[38]  Xin Li,et al.  Transformation Networks for Target-Oriented Sentiment Classification , 2018, ACL.

[39]  Xiaokui Xiao,et al.  Coupled Multi-Layer Attentions for Co-Extraction of Aspect and Opinion Terms , 2017, AAAI.

[40]  Arjun Mukherjee,et al.  Aspect Extraction with Automated Prior Knowledge Learning , 2014, ACL.

[41]  Martín Abadi,et al.  TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems , 2016, ArXiv.

[42]  Qian Liu,et al.  Automated Rule Selection for Aspect Extraction in Opinion Mining , 2015, IJCAI.

[43]  Bin Wang,et al.  Improving Aspect Term Extraction With Bidirectional Dependency Tree Representation , 2018, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[44]  Harith Alani,et al.  Automatically Extracting Polarity-Bearing Topics for Cross-Domain Sentiment Classification , 2011, ACL.

[45]  Christoph Goller,et al.  Learning task-dependent distributed representations by backpropagation through structure , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

[46]  Hwee Tou Ng,et al.  An Unsupervised Neural Attention Model for Aspect Extraction , 2017, ACL.

[47]  Xiaodong Gu,et al.  Aspect-based Opinion Summarization with Convolutional Neural Networks , 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

[48]  Ting Liu,et al.  Aspect Level Sentiment Classification with Deep Memory Network , 2016, EMNLP.