A curated collection of research on knowledge graphs
Leveraging Multi-token Entities in Document-level Named Entity Recognition AAAI 2020. Hu et al. [Paper]
Robust Named Entity Recognition with Truecasing Pretraining. AAAI 2020. Mayhew et al. [Paper]
Multi-grained Named Entity Recognition. ACL 2019. Xia, Congying and Zhang, Chenwei and Yang, Tao and Li, Yaliang and Du, Nan and Wu, Xian and Fan, Wei and Ma, Fenglong and Philip, S Yu. [Paper]
Neural architectures for named entity recognition. NAACL 2017. Lample, Guillaume and Ballesteros, Miguel and Subramanian, Sandeep and Kawakami, Kazuya and Dyer, Chris. [Paper] [Cdde] [Code]
Named entity recognition with bidirectional LSTM-CNNs. TACL 2016. Chiu, Jason PC and Nichols, Eric. [Paper]
Novel Entity Discovery from Web Tables WWW 2020. Zhang et al. [Paper]
MetaNER: Named Entity Recognition with Meta-Learning WWW 2020. Li et al. [Paper]
Collective Multi-type Entity Alignment Between Knowledge Graphs WWW 2020. Zhu et al. [Paper]
Entity Alignment between Knowledge Graphs Using Attribute Embeddings. AAAI 2019. Trsedya, Bayu Distiawan and Qi, Jianzhong and Zhang, Rui. [Paper] [Code]
Multi-view Knowledge Graph Embedding for Entity Alignment. IJCAI 2019. Zhang, Qingheng and Sun, Zequn and Hu, Wei and Chen, Muhao and Guo, Lingbing and Qu, Yuzhong. [Paper] [Code]
Co-training embeddings of knowledge graphs and entity descriptions for cross-lingual entity alignment. IJCAI 2018. Chen, Muhao and Tian, Yingtao and Chang, Kai-Wei and Skiena, Steven and Zaniolo, Carlo. [Paper]
Bootstrapping Entity Alignment with Knowledge Graph Embedding. IJCAI 2018. Zequn Sun, Wei Hu, Qingheng Zhang and Yuzhong Qu. [Paper] [Code] [Note]
Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networks. EMNLP 2018. Zhichun Wang, Qingsong Lv, Xiaohan Lan, Yu Zhang. [Paper]
Cross-lingual entity alignment via joint attribute-preserving embedding. ISWC 2017. Sun, Zequn and Hu, Wei and Li, Chengkai. [Paper]
Iterative entity alignment via joint knowledge embeddings. IJCAI 2017. Zhu, Hao and Xie, Ruobing and Liu, Zhiyuan and Sun, Maosong. [Paper] [Code]
Multilingual knowledge graph embeddings for cross-lingual knowledge alignment. IJCAI 2017. Chen, Muhao and Tian, Yingtao and Yang, Mohan and Zaniolo, Carlo. [Paper]
Aligning Knowledge Base and Document Embedding Models Using Regularized Multi-Task Learning. ISWC 2018. Baumgartner, Matthias and Zhang, Wen and Paudel, Bibek and Dell’Aglio, Daniele and Chen, Huajun and Bernstein, Abraham. [Paper]
High Quality Candidate Generation and Sequential Graph Attention Network for Entity Linking WWW 2020. Fang et al. [Paper]
Dynamic Graph Convolutional Networks for Entity Linking WWW 2020. Wu et al. [Paper]
Improving Entity Linking by Modeling Latent Relations between Mentions. ACL 2018. Le, Phong and Titov, Ivan. [Paper]
Deep Joint Entity Disambiguation with Local Neural Attention. EMNLP 2017. Ganea, Octavian-Eugen and Hofmann, Thomas. [Paper]
Design challenges for entity linking. TACL 2015. Ling, Xiao and Singh, Sameer and Weld, Daniel S. [Paper]
Leveraging deep neural networks and knowledge graphs for entity disambiguation. 2015. Huang, Hongzhao and Heck, Larry and Ji, Heng. [Paper]
Entity disambiguation by knowledge and text jointly embedding. CoNLL 2016. Fang, Wei and Zhang, Jianwen and Wang, Dilin and Chen, Zheng and Li, Ming. [Paper]
End-to-End Neural Entity Linking. CoNLL 2018. Nikolaos Kolitsas, Octavian-Eugen Ganea, Thomas Hofmann [Paper]
Label noise reduction in entity typing by heterogeneous partial-label embedding. KDD 2016. Ren, Xiang and He, Wenqi and Qu, Meng and Voss, Clare R and Ji, Heng and Han, Jiawei. [Paper]
Label Embedding for Zero-shot Fine-grained Named Entity Typing. COLING 2016. Yukun Ma, Erik Cambria, Sa Gao. [Paper] [Code]