请查收!顶会AAAI 2020录用论文之知识图谱篇

欢迎关注语言智能技术笔记簿微信公众号

导读:人工智能领域顶级会议AAAI 2020持续火爆,共收到有效论文投稿8843篇,其中7737篇论文进入评审环节,最终收录1591篇,收录率为 20.6%。较去年16.2%的收录率,投稿数多了将近1100篇,收录论文数量多了400多篇。本系列文章主要对今年录用的论文按照研究主题进行划分,为相关领域的爱好者们给予便利,省去检索论文的烦恼。本届会议中的优秀论文会在<一起读论文>栏目中进行详细解读,尽请关注!

知识图谱篇(Knowledge Graph)

Graph Completion

1322: Improving Entity Linking by Modeling Latent Entity Type Information
Shuang Chen; Jinpeng Wang; Feng Jiang; Chin-Yew Lin
Harbin Institute of Technology; Microsoft Research Asia;

3019: Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
Zhanqiu Zhang; Jianyu Cai; Yongdong Zhang; Jie Wang
University of Science and Technology of China;

8971: Contextual Parameter Generation for Knowledge Graph Link Prediction
George Stoica; Otilia Stretcu; Anthony Platanios; Tom Mitchell; Barnabas Poczos
Carnegie Mellon University

9004: Bursting the Filter Bubble: Fairness-Aware Network Link Prediction
Farzan Masrour; Tyler Wilson; Pang-Ning Tan; Heng Yan; Abdol Esfahanian
Michigan State University

4420: LATTE: Latent Type Modeling for Biomedical Entity Linking
Ming Zhu; Busra Celikkaya; Parminder Bhatia; Chandan K Reddy
Virginia Tech; Amazon;

5535: A Recurrent Model for Collective Entity Linking with Adaptive Features
Xiaoling Zhou; Yukai Miao; Wei Wang; Jianbin Qin
University of New South Wales

6492: Simultaneously Linking Entities and Extracting Relations from Biomedical Text without Mention-level Supervision
Trapit Bansal; Patrick Verga; Neha Choudhary; Andrew McCallum
University of Massachusetts Amherst

8427: Type-aware Anchor Link Prediction across Heterogeneous Networks based on Graph Attention Network
Xiaoxue Li; Yanmin Shang; Yanan Cao; Yangxi Li; Jianlong Tan; Yanbing Liu
Chinese Academy of Sciences

9347: Fine-Grained Entity Typing for Domain Independent Entity Linking
Yasumasa Onoe; Greg Durrett
University of Texas Austin

9502: Commonsense Knowledge Base Completion with Structural and Semantic Context
Chaitanya Malaviya; Chandra Bhagavatula; Antoine Bosselut; Yejin Choi
Allen Institute for Artificial Intelligence; University of Washington

9358: Diachronic Embedding for Temporal Knowledge Graph Completion
Rishab Goel; Seyed Mehran Kazemi; Marcus Brubaker; Pascal Poupart
Borealis AI

2278: Few-Shot Knowledge Graph Completion
Chuxu Zhang; Huaxiu Yao; Chao Huang; Meng Jiang; Zhenhui (Jessie) Li; Nitesh Chawla
University of Notre Dame; Pennsylvania State University;

4020: ParamE: Regarding Neural Network Parameters as Relation Embeddings for Knowledge Graph Completion
Feihu Che; Dawei Zhang; Jianhua Tao; Mingyue Niu; Bocheng Zhao
Chinese Academy of Sciences; University of Chinese Academy of Sciences;

6756: Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion
Zhao Zhang; Fuzhen Zhuang; Hengshu Zhu; Zhiping Shi; Hui Xiong; Qing He
Chinese Academy of Sciences; Baidu Inc.; Capital Normal University; The State University of New Jersey

Entity and Relation Learning and Extraction

3203: Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction
Yang Li; Guodong Long; Tao Shen; Tianyi Zhou; Lina Yao; Huan Huo; Jing Jiang
University of Technology Sydney; University of Washington; University of New South Wales;

3868: Improving Neural Relation Extraction with Positive and Unlabeled Learning
Zhengqiu He; Wenliang Chen; Yuyi Wang; Wei Zhang; Guanchun Wang; Min Zhang
Soochow University; ETH Zurich; Laiye Startup;

133: Are Noisy Sentences Useless for Distant Supervised Relation Extraction?
Yu-Ming Shang; Heyan Huang; Xian-Ling Mao; Xin Sun; Wei Wei
Bit; Beijing Institute of Technology; Huazhong University of Science and Technology

4412: CopyMTL: Copy Mechanism for Joint Extraction of Entities and Relations with Multi-Task Learning
Daojian Zeng; Haoran Zhang; Qianying Liu
Changsha University of Science and Technology; University of Illinois Urbana-Champaign; Kyoto University

5816: Relation Extraction with Convolutional Network over Learnable Syntax-Transport Graph
Kai Sun; Richong Zhang; Yongyi Mao; Samuel Mensah; Xudong Liu
Beihang University; University of Ottawa;

5895: Relation Extraction Exploiting Full Dependency Forests
Lifeng Jin; Linfeng Song; Yue Zhang; Kun Xu; Wei-yun Ma; Dong Yu
The Ohio State University; Tencent; Westlake University; Academia Sinica

6937: Multi-view Consistency for Relation Extraction via Mutual Information and Structure Prediction
Amir Pouran Ben Veyseh; Franck Dernoncourt; My Thai; Dejing Dou; Thien Nguyen
University of Oregon; Adobe Research; University of Florida

7408: Distilling Knowledge from Well-informed Soft Labels for Neural Relation Extraction
Zhenyu Zhang; Xiaobo Shu; Bowen Yu; Tingwen Liu; Jiapeng Zhao; Quangang Li; Li Guo
Chinese Academy of Sciences; University of Chinese Academy of Sciences

7540: Joint Entity and Relation Extraction with a Hybrid Transformer and Reinforcement Learning Based Model
Ya Xiao; Chengxiang Tan; Zhijie Fan; Qian Xu; Wenye Zhu
Tongji University; The Third Research Institute of the Ministry of Public Security

7819: Integrating Relation Constraints with Neural Relation Extractors
Yuan Ye; Yansong Feng; Bingfeng Luo; Yuxuan Lai; Dongyan Zhao
Peking University

10036: Effective Modeling of Encoder-Decoder Architecture for Joint Entity and Relation Extraction
Tapas Nayak; Hwee Tou Ng
National University of Singapore

7793: Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs
Pengda Qin; Xin Wang; Wenhu Chen; Chunyun Zhang; Weiran Xu; William Yang Wang
Beijing University of Posts and Telecommunications; University of California, Santa Barbara; Shandong University of Finance and Economics

4433: Neural Snowball for Few-Shot Relation Learning
Tianyu Gao; Xu Han; Ruobing Xie; Zhiyuan Liu; Fen Lin; Leyu Lin; Maosong Sun
Tsinghua University; Tencent

Graph Alignment

3162: Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation
Zequn Sun; Chengming Wang; Wei Hu; Muhao Chen; Jian Dai; Wei Zhang; Yuzhong Qu
Nanjing University; University of Pennsylvania; Alibaba Group;

7248: Coordinated Reasoning for Cross-Lingual Knowledge Graph Alignment
Kun Xu; Linfeng Song; Yansong Feng; Yan Song; Dong Yu
Tencent AI Lab; Peking University

8586: COTSAE: CO-Training of Structure and Attribute Embeddings for Entity Alignment
Kai Yang; Shaoqin Liu; Junfeng Zhao; Yasha Wang; Bing Xie
Peking University

Graph Embedding

8986: InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions
Shikhar Vashishth; Soumya Sanyal; Vikram Nitin; Nilesh Agrawal; Partha Talukdar
Indian Institute of Science; Columbia University;

4560: Rule-Guided Compositional Representation Learning on Knowledge Graphs
Guanglin Niu; Yongfei Zhang; Bo Li; Peng Cui; Si Liu; Jingyang Li; Xiaowei Zhang
Beihang University; Tsinghua University; Qingdao University

4000: Learning Triple Embeddings from Knowledge Graphs
Valeria Fionda; Giuseppe Pirrò
DeMACs; University of Calabria; University of Rome “La Sapienza”

KBQA

3419: Skeleton-based Semantic Parsing for Complex Questions over Knowledge Bases
Yawei Sun; Lingling Zhang; Gong Cheng; Yuzhong Qu
Nanjing University

3330: Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering
Shangwen Lv; Daya Guo; Jingjing Xu; Duyu Tang; Nan Duan; Ming Gong; Linjun Shou; Daxin Jiang; Guihong Cao; Songlin Hu
Chinese Academy of Sciences; Sun-Yat Sen University; Peking University; Microsoft Research;

General/Other

10313: GraphER: Token-Centric Entity Resolution with Graph Convolutional Neural Networks
Bing Li; Wei Wang; Yifang Sun; Linhan Zhang; Muhammad Asif Ali; Yi Wang
University of New South Wales; Dongguan University of Technology

2775: Reasoning on Knowledge Graphs with Debate Dynamics
Marcel Hildebrandt; Jorge Andres Quintero Serna; Yunpu Ma; Martin Ringsquandl; Mitchell Joblin; Volker Tresp
Siemens; Ludwig Maximilian University of Munich

5161: Knowledge Graph Transfer Network for Few-Shot Recognition
Riquan Chen; Tianshui Chen; Xiaolu Hui; Hefeng Wu; Guanbin Li; Liang Lin
Sun Yat-Sen University; DarkMatter AI

想要了解更多的自然语言处理最新进展、技术干货及学习教程,欢迎关注微信公众号“语言智能技术笔记簿”或扫描二维码添加关注。
在这里插入图片描述

發表評論
所有評論
還沒有人評論,想成為第一個評論的人麼? 請在上方評論欄輸入並且點擊發布.
相關文章