NLP论文笔记合集（持续更新）

经典论文

2003年发表的文章${}^1$，NLP经典论文：NNLM 笔记
2013年发表的文章${}^2$，NLP经典论文：Word2vec、CBOW、Skip-gram 笔记
2014年发表的文章${}^3$，NLP经典论文：Sequence to Sequence、Encoder-Decoder 、GRU 笔记
2014年发表的文章${}^4$，NLP经典论文：TextCNN 笔记
2014年发表的文章${}^5$，NLP经典论文：最早的提出attention模型的文章 笔记
2015年发表的文章${}^6$，NLP、CV经典论文：Batch Normalization 笔记
2016年发表的文章${}^7$，NLP经典论文：FastText 笔记
2016年发表的文章${}^8$，NLP经典论文：Layer Normalization 笔记
2017年发表的文章${}^9$，NLP经典论文：Attention、Self-Attention、Multi-Head Attention、Transformer 笔记
2018年发表的文章${}^{10}$，NLP经典论文：ELMo 笔记
2018年发表的文章${}^{11}$，NLP经典论文：BERT 笔记

参考文献

[1] Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Jauvin. A neural probabilistic language model. Journal of machine learning research, 3(Feb):1137–1155, 2003.

[2] Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781, 2013.

[3] Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. Learning phrase representations using rnn encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078, 2014.

[4] Y. Kim. Convolutional neural networks for sentence classification. Eprint Arxiv, 2014.

[5] Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473, 2014.

[6] Sergey Ioffe and Christian Szegedy. Batch normalization: Accelerating deep network training by reducing internal covariate shift. In International conference on machine learning, pages 448–456. PMLR, 2015.

[7] Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov. Bag of tricks for efficient text classification. arXiv preprint arXiv:1607.01759, 2016.

[8] Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton. Layer normalization. arXiv preprint arXiv:1607.06450, 2016.

[9] Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. Attention is all you need. In Advances in neural information processing systems, pages 5998–6008, 2017.

[10] Matthew Peters, M. Neumann, M. Iyyer, M. Gardner, and L. Zettlemoyer. Deep contextualized word representations. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), 2018.

[11] Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805, 2018.

情感分析论文

关键词

aspect-based、aspect-level、aspect-oriented、aspect detection、emotional、sentiment analysis、sentiment classification、online reviews、opinion mining、

综述

2015年10月01日发表的文章${}^1$，NLP论文（情感分析）：《Survey on Aspect-Level Sentiment Analysis》 笔记
2016年03月17日发表的文章${}^2$，NLP论文（情感分析）：《Affective Computing and Sentiment Analysis》 笔记

参考文献

[1] Kim Schouten and Flavius Frasincar. Survey on aspect-level senti-ment analysis. IEEE Transactions on Knowledge and Data Engineering, 28(3):813–830, 2016.
[2] Erik Cambria. Affective computing and sentiment analysis. IEEE In-telligent Systems, 31(2):102–107, 2016.

非综述

2018年01月01日发表的文章${}^1$，NLP论文（情感分析）：《Deep Convolution Neural Networks for Twitter Sentiment Analysis》 笔记
2018年02月15日发表的文章${}^2$，NLP论文（情感分析）：《Hate Speech on Twitter: A Pragmatic Approach to Collect Hateful and Offensive Expressions and Perform Hate Speech Detection》 笔记
2018年11月15日至17日会议发表的文章${}^3$，NLP论文（情感分析）：《Aspect Detection and Sentiment Classification Using Deep Neural Network for Indonesian Aspect-Based Sentiment Analysis》 笔记
2020年01月28日发表的文章${}^4$，NLP论文（情感分析）：《Aspect-Based Sentiment Classification Using Interactive Gated Convolutional Network》 笔记
2020年06月29日发表的文章${}^5$，NLP论文（情感分析）：《Convolutional multi-head self-attention on memory for aspect sentiment classification》 笔记
2020年07月21日发表的文章${}^6$，NLP论文（情感分析）：《ADeCNN: An Improved Model for Aspect-Level Sentiment Analysis Based on Deformable CNN and Attention》 笔记
2020年10月16日至18日会议发表的文章${}^7$，NLP论文（情感分析）：《Aspect Based Sentiment Analysis with Self-Attention and Gated Convolutional Networks》 笔记
2020年10月16日至19日会议发表的文章${}^8$，NLP论文（情感分析）：《Aspect sentiment analysis based on gating convolutional network and attention weighting mechanism》 笔记
2020年11月17日至20日会议发表的文章${}^9$，NLP论文（情感分析）：《One Belt, One Road, One Sentiment? A Hybrid Approach to Gauging Public Opinions on the New Silk Road Initiative》 笔记
2020年11月13日至15日会议发表的文章${}^{10}$，NLP论文（情感分析）：《LSTM-Gate CNN network for Aspect Sentiment Analysis》 笔记
2021年01月19日发表的文章${}^{11}$，NLP论文（情感分析）：《Combination of Convolutional Neural Network and Gated Recurrent Unit for Aspect-Based Sentiment Analysis》 笔记
2021年04月08日至10日会议发表的文章${}^{12}$，NLP论文（情感分析）：《Aspect-Oriented Sentiment Classification using BiGRU-CNN model》 笔记
2021年06月25日至27日会议发表的文章${}^{13}$，NLP论文（情感分析）：《Aspect Based Opinion Mining Leveraging Weighted BiGRU and CNN Module in Parallel》 笔记
2021年07月18日至22日会议发表的文章${}^{14}$，NLP论文（情感分析）：《A Novel Bi-Branch Graph Convolutional Neural Network for Aspect Level Sentiment Classification》 笔记

参考文献

[1] Zhao Jianqiang, Gui Xiaolin, and Zhang Xuejun. Deep convolution neural networks for twitter sentiment analysis. IEEE Access, 6:23253–23260, 2018.
[2] Hajime Watanabe, Mondher Bouazizi, and Tomoaki Ohtsuki. Hate speech on twitter: A pragmatic approach to collect hateful and offensive expressions and perform hate speech detection. IEEE Access, 6:13825–13835, 2018.
[3] Arfinda Ilmania, Abdurrahman, Samuel Cahyawijaya, and Ayu Pur-warianti. Aspect detection and sentiment classification using deep neu-ral network for indonesian aspect-based sentiment analysis. In 2018 International Conference on Asian Language Processing (IALP), pages 62–67, 2018.
[4] Avinash Kumar, Vishnu Teja Narapareddy, Veerubhotla Aditya Srikanth, Lalita Bhanu Murthy Neti, and Aruna Malap-ati. Aspect-based sentiment classification using interactive gated convolutional network. IEEE Access, 8:22445–22453, 2020.
[5] Yaojie Zhang, Bing Xu, and Tiejun Zhao. Convolutional multi-head self-attention on memory for aspect sentiment classification. IEEE/CAA Journal of Automatica Sinica, 7(4):1038–1044, 2020.
[6] Jie Zhou, Siqi Jin, and Xinli Huang. Adecnn: An improved model for aspect-level sentiment analysis based on deformable cnn and attention. IEEE Access, 8:132970–132979, 2020.
[7] Jian Yang and Juan Yang. Aspect based sentiment analysis with self-attention and gated convolutional networks. In 2020 IEEE 11th In-ternational Conference on Software Engineering and Service Science (ICSESS), pages 146–149, 2020.
[8] Fan Xu and Xuezhong Qian. Aspect sentiment analysis based on gat-ing convolutional network and attention weighting mechanism. In 2020 19th International Symposium on Distributed Computing and Applica-tions for Business Engineering and Science (DCABES), pages 54–57, 2020.
[9] Jonathan Kevin Chandra, Erik Cambria, and Andrea Nanetti. One belt, one road, one sentiment? a hybrid approach to gauging public opinions on the new silk road initiative. In 2020 International Confer-ence on Data Mining Workshops (ICDMW), pages 7–14, 2020.
[10] Shuhua Cao and Pengxiang Gao. Lstm-gate cnn network for aspect sentiment analysis. In 2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT), pages 443–447, 2020.
[11] Narisa Zhao, Huan Gao, Xin Wen, and Hui Li. Combination of con-volutional neural network and gated recurrent unit for aspect-based sentiment analysis. IEEE Access, 9:15561–15569, 2021.
[12] Sindhu C, Bihanga Som, and Samar Pratap Singh. Aspect-oriented sentiment classification using bigru-cnn model. In 2021 5th Interna-tional Conference on Computing Methodologies and Communication (ICCMC), pages 984–989, 2021.
[13] C Sindhu, Bihanga Som, and Samar Pratap Singh. Aspect based opin-ion mining leveraging weighted bigru and cnn module in parallel. In 2021 International Conference on Intelligent Technologies (CONIT), pages 1–7, 2021.
[14] Bingliang Chen, Guojun Lu, Yun Xue, and Qianhua Cai. A novel bi-branch graph convolutional neural network for aspect level sentiment classification. In 2021 International Joint Conference on Neural Net-works (IJCNN), pages 1–8, 2021.

其他论文

2016年发表的文章${}^1$，NLP论文：Weight tying 笔记
2019年发表的文章${}^2$，NLP论文：BERT各层表示在不同NLP任务上的解释 笔记

参考文献

[1] Ofir Press and Lior Wolf. Using the output embedding to improve language models. arXiv preprint arXiv:1608.05859, 2016.

[2] Ian Tenney, Dipanjan Das, and Ellie Pavlick. Bert rediscovers the clas-sical nlp pipeline. arXiv preprint arXiv:1905.05950, 2019.