JLU-CCST-数据库与web智能-信息抽取&情感分析小组

论文 && 代码清单

1.关系抽取 RE

2020/09/24

Paper

• A review of relation extraction. PDF

• Relation Classification via Convolutional Deep Neural Network. 2014. PDF

• Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks. ACL 2015. PDF | 代码

• Neural Relation Extraction with Selective Attention over Instances. 2016. PDF|代码1 | 代码2

• Distant Supervision for Relation Extraction with Sentence-Level Attention and Entity Descriptions. AAAI 2017. PDF | 代码

• Open Relation Extraction : Relational Knowledge Transfer from Supervised Data to Unsupervised Data. PDF | 代码

• Yang Li, et al. Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction. AAAI 2020:8269-8276. PDF

• Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism. PDF | 代码

Blog

• 信息抽取-关系抽取

2020/10/09

Paper

• 鄂海红，张文静，肖思琪，程瑞，胡莺夕，周筱松, 牛佩晴.深度学习实体关系抽取研究综述.软件学报,2019,3(6):1793-1818. PDF

• WANG Chuandong, XU Jiao, ZHANG Yong. Survey of entity relation extraction. Computer Engineering and Applications.[J] 2020. 56(12):25-36. PDF

• Long Bai, Xiaolong Jin, Chuanzhi Zhuang, et al. Entity Type Enhanced Neural Model for Distantly Supervised Relation Extraction (Student Abstract)[C]. AAAI 2020: 13751-13752. PDF

• Zhepei Wei, Jianlin Su, Yue Wang, et al. A Novel Cascade Binary Tagging Framework for Relational Triple Extraction[C]. ACL 2020: 1476-1488. PDF | 代码1 | 代码2

• Tianyun Gao,Xu Han,Ruobing Xie,Zhiyuan Liu,Fen Lin,Leyu Lin,Maosong Sun.Neural Snowball for Few-Shot Relation Learning[C]. AAAI-20. PDF | 代码

• Hu, Linmei et al. Improving Distantly-Supervised Relation Extraction with Joint Label Embedding. EMNLP/IJCNLP (2019). PDF

Blog

• 关系抽取之远程监督算法

• Relation Extration

2020/10/16

Paper

• More Data, More Relations, More Context and More Openness:A Review and Outlook for Relation Extraction.PDF

• Shen Y, Tan S, Sordoni A, et al. Ordered neurons: Integrating tree structures into recurrent neural networks[C]. ICLR 2019. PDF | 代码

2020/10/23

Paper

• Xu Han,Hao Zhu,Pengfei Yu,Ziyun Wang,Yuan Yao,Zhiyuan Liu,Maosong Sun. FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation. PDF

• Tianyu Gao,Xu Han,Hao Zhu,Zhiyuan Liu,Peng Li,Maosong Sun,Jie Zhou. FewRel 2.0: Towards More Challenging Few-Shot Relation Classifification.PDF

• Peng Zhou, Wei Shi, Jun Tian, Zhenyu Qi, Bingchen Li, Hongwei Hao, Bo Xu.Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classifification. ACL 2016. PDF | 代码

• Tianyu Gao,Xu Han,Zhiyuan Liu,Maosong Sun.AAAI2019. Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification. PDF | 代码

• Jake Snell,Kevin Swersky,Richard Zemel.Prototypical Networks for Few-shot Learning. PDF | 代码

2020/10/30

Paper

• C´ ıcero Nogueira dos Santos，Bing Xiang，Bowen Zhou.Classifying Relations by Ranking with Convolutional Neural Networks.ACL2015. PDF | 代码1 | 代码2

• Livio Baldini Soares, Nicholas FitzGerald,Jeffrey Ling,Tom Kwiatkowski.Matching the Blanks: Distributional Similarity for Relation Learning.ACL2019. PDF

• Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification. PDF | 代码

2020/11/06

Paper

• Yao Y , Ye D , Li P , et al. DocRED: A Large-Scale Document-Level Relation Extraction Dataset[C]// Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. ACL2019. PDF

• Yu D , Sun K , Cardie C , et al. Dialogue-Based Relation Extraction[J].ACL2020. PDF

• Zhang Yuanzhe,Jiang Zhongtao,Zhang Tao,Liu Shiwan,Cao Jiarun,Cao Kang,Liu Shengping,Zhao Jun. MIE: A Medical Information Extractor towards Medical Dialogues.ACL2020. PDF | 代码

• Yu Haiyang,Zhang Ningyu,Deng Shumin,Ye Hongbin,Zhang Wei,Chen Huajun.Bridging Text and Knowledge with Multi-Prototype Embedding for Few-Shot Relational Triple Extraction.COLING 2020. PDF

2020/11/13

Paper

• Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification. PDF | 代码

• Enhanced LSTM for Natural Language Inference. PDf | 代码

• J. Moreira, C. Oliveira, D. Macêdo, C. Zanchettin and L. Barbosa. Distantly-Supervised Neural Relation Extraction with Side Information using BERT. 2020 IJCNN. PDF

2020/11/20

Paper

• Dialogue-Based Relation Extraction. PDF | 代码

• Lifeng Jin，Linfeng Song, Yue Zhang, Kun Xu, Wei-yun Ma，Dong Yu. Relation Extraction Exploiting Full Dependency Forests.AAAI 2020. PDF | 代码

• Induction Networks for Few-Shot Text Classifification. PDF | 代码

• Dynamic Routing Between Capsules. PDF | 代码

• Yuan Y, Liu L, Tang S, et al. Cross-relation cross-bag attention for distantly-supervised relation extraction[C].AAAI 2019. PDF

2020/11/27

Paper

• Dialogue Relation Extraction with Document-level Heterogeneous Graph Attention Networks. PDF | 代码

• Dat Quoc Nguyen,Karin Verspoor. Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings.ACL 2018. PDF

• Dynamic Memory Induction Networks for Few-Shot Text Classification.2020 ACL. PDF

• Hierarchical Attention Prototypical Networks for Few-Shot Text Classification. ACL 2019. PDF

• Ding Z, Xia R, Yu J. ECPE-2D: Emotion-Cause Pair Extraction based on Joint Two-Dimensional Representation, Interaction and Prediction[C]//ACL 2020. PDF | 代码

2.情感分析

2020/09/24

Paper

• KinGDOM: Knowledge-Guided DOMain Adaptation for Sentiment Analysis. ACL 2020. PDF | 代码

• Targeted Aspect-Based Sentiment Analysis via Embedding Commonsense Knowledge into an Attentive LSTM. PDF | 代码

Blog

• 情感分析-1

• 情感分析-2

• 情感分析-3

2020/10/09

Paper

• Poria S , Hazarika D , Majumder N , et al. Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis Research. 2020. PDF

• Liu F, Cohn T, Baldwin T. Recurrent entity networks with delayed memory update for targeted aspect-based sentiment analysis[C]. NAACL 2018: 278-283. PDF | 代码

• Bosselut A, Rashkin H, Sap M, et al. COMET: Commonsense transformers for automatic knowledge graph construction[C]. ACL 2019: 4762-4779. PDF | 代码 | 图谱

• Saeidi, M.; Bouchard, G.; Liakata, M.; and Riedel, S. 2016. Sentihood: Targeted aspect based sentiment analysis dataset for urban neighbourhoods[C]. In COLING 2016: 1546–1556. PDF |数据集

• Sun C, Huang L, Qiu X. Utilizing BERT for aspect-based sentiment analysis via constructing auxiliary sentence[C]. NAACL 2019: 380-385. PDF | 代码

• Cambria E, Poria S, Bajpai R, et al. SenticNet 4: A semantic resource for sentiment analysis based on conceptual primitives[C]. In COLING 2016: 2666-2677. PDF | 代码

2020/10/16

Paper

• Shenoy A , Sardana A . Multilogue-Net: A Context Aware RNN for Multi-modal Emotion Detection and Sentiment Analysis in Conversation[C]// The 58th Annual Meeting of the Association for Computational Linguistics. 2020. PDF | 代码

2020/10/23

Paper

• Ghosal D , Akhtar M S , Chauhan D , et al. Contextual Inter-modal Attention for Multi-modal Sentiment Analysis[C]// Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 2018. PDF |代码

• Zhao H, Huang L, Zhang R, et al. SpanMlt: A Span-based Multi-Task Learning Framework for Pair-wise Aspect and Opinion Terms Extraction[C]. ACL. 2020: 3239-3248. PDF

• Chen S, Liu J, Wang Y, et al. Synchronous Double-channel Recurrent Network for Aspect-Opinion Pair Extraction[C]. ACL. 2020: 6515-6524. PDF | 代码

2020/11/13

Paper

• Chen Z, Qian T. Relation-Aware Collaborative Learning for Unified Aspect-Based Sentiment Analysis[C]. ACL. 2020: 3685-3694. PDF | 代码

2020/11/20

Paper

• Poria S , Hazarika D , Majumder N , et al. MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations[J]. 2019 ACL. PDF | 代码1 | 代码2

• Soares L B, FitzGerald N, Ling J, et al. Matching the Blanks: Distributional Similarity for Relation Learning[C] . ACL. 2020: 2895-2905. PDF | 代码

2020/11/27

Paper

• Ghosal D , Majumder N , Poria S , et al. DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation[J]. 2019. PDF | 代码

• Mikael Henaff, Jason Weston1, Arthur Szlam1, et al. Tracking the World State with Recurrent Entity Networks[C]. ICLR 2017. PDF | 代码

3.命名实体识别 NER

4.事件抽取

5.Entity Typing

6.其他

Paper

• Attention Is All You Need. 2017. PDF

Blog

• 交叉熵-1
• 交叉熵-2
• 为什么交叉熵可用于计算代价
• 交叉熵在机器学习中的使用-1
• 交叉熵在机器学习中的使用-2
• 条件熵
• 对抗训练
• Transformer
• 识别猫的简单神经网络
• Fine-tune
• 孪生网络
• 北航大数据高精尖研究中心_信息抽取
• TextCNN相关知识-1
• TextCNN相关知识-2 *虚拟对抗训练
• Lipschitz约束
• 神经网络
• 如何深度理解RNN
• Dropout解决过拟合问题-1
• Dropout解决过拟合问题-2
• 网格搜索grid search
• 通俗理解条件熵
• pytorch学习课程视频
• pytorch学习，训练LSTM网络构建语言模型
• LSTM & GRU
• 理解胶囊网络-1
• 理解胶囊网络-2