第58届国际计算语言学协会年会（ACL，The Association for Computational Linguistics）将于2020年7月6号-8号线上举行。官网公布了ACL2020的论文收录名单，共计收录778篇论文，本次ACL大会共提交了3429篇论文，长文录取率为25%。作为自然语言处理（NLP）领域的顶会，其中有一些涉及NLP技术的推荐系统论文也会投稿于此。
第37届机器学习国际会议（ICML，International Conference on Machine Learning）将于2020年7月12日至18日线上举行。官网公布了ICML2020的论文收录名单，共计收录1088篇论文，本次ICML大会共提交了4990篇论文，录取率为21.8%。
推荐相关论文列表
本次ACL2020大会共整理出5篇关于推荐系统的论文，其中涉及到2篇对话推荐系统和3篇新闻推荐系统。值得注意的是，3篇新闻推荐系统论文均来自于MSRA谢幸老师团队，太强了(●'◡'●)。不难发现，由于ACL为自然语言处理相关的会议，所以推荐系统的比重较小，另外，接收的推荐系统论文中都涉及NLP相关的技术。
另外，本篇文章还整理出了ICML2020中关于推荐系统的论文4篇。其中涉及GCN、非负矩阵分解等技术。
由于在研究推荐系统的时候，也会用到图神经网络以及知识图谱相关的知识，因此后两部分也整理了相关的论文。
推荐系统-ACL2020
- Dynamic Online Conversation Recommendation
https://www.aclweb.org/anthology/2020.acl-main.305.pdf https://github.com/zxshamson/dy-conv-rec
- Towards Conversational Recommendation over Multi-Type Dialogs
https://www.aclweb.org/anthology/2020.acl-main.98.pdf https://github.com/PaddlePaddle/models/
- Fine-grained Interest Matching for Neural News Recommendation
https://www.aclweb.org/anthology/2020.acl-main.77.pdf
- Graph Neural News Recommendation with Unsupervised Preference Disentanglement
https://www.aclweb.org/anthology/2020.acl-main.392.pdf
- MIND: A Large-scale Dataset for News Recommendation
https://www.aclweb.org/anthology/2020.acl-main.331.pdf https://github.com/zxshamson/dy-conv-rec
推荐系统-ICML2020
- Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters
https://arxiv.org/abs/2006.15516.pdf
- Optimization and Analysis of the pAp@k Metric for Recommender Systems
- Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach
- Ordinal Non-negative Matrix Factorization for Recommendation
https://arxiv.org/pdf/2006.01034.pdf
网络表示学习&图神经网络相关
- Learning to Ask More: Semi-Autoregressive Sequential Question Generation under Dual-Graph Interaction.
- Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks.
- GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media.
- Integrating Semantic and Structural Information with Graph Convolutional Network for Controversy Detection.
- Line Graph Enhanced AMR-to-Text Generation with Mix-Order Graph Attention Networks.
- Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases.
- A Graph Auto-encoder Model of Derivational Morphology.
- AMR Parsing via Graph-Sequence Iterative Inference.
- Semantic Graphs for Generating Deep Questions.
- A Novel Graph-based Multi-modal Fusion Encoder for Neural Machine Translation.
- Relational Graph Attention Network for Aspect-based Sentiment Analysis.
- Syntax-Aware Opinion Role Labeling with Dependency Graph Convolutional Networks.
- Entity-Aware Dependency-Based Deep Graph Attention Network for Comparative Preference Classification.
- Heterogeneous Graph Neural Networks for Extractive Document Summarization.
- Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification.
- Document Modeling with Graph Attention Networks for Multi-grained Machine Reading Comprehension.
- Aligned Dual Channel Graph Convolutional Network for Visual Question Answering.
- Multimodal Neural Graph Memory Networks for Visual Question Answering.
- Fine-grained Fact Verification with Kernel Graph Attention Network
- Continuous Graph Neural Networks
知识图谱
- Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases.
- Grounded Conversation Generation as Guided Traverses in Commonsense Knowledge Graphs.
- Can We Predict New Facts with Open Knowledge Graph Embeddings? A Benchmark for Open Link Prediction.
- The Dialogue Dodecathlon: Open-Domain Knowledge and Image Grounded Conversational Agents.
- Knowledge Graph Embedding Compression.
- Orthogonal Relation Transforms with Graph Context Modeling for Knowledge Graph Embedding.
- Breaking Through the 80% Glass Ceiling: Raising the State of the Art in Word Sense Disambiguation by Incorporating Knowledge Graph Information.
- SEEK: Segmented Embedding of Knowledge Graphs.
- SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis.
- Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings.
- Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward.
- A Re-evaluation of Knowledge Graph Completion Methods.
- ReInceptionE: Relation-Aware Inception Network with Joint Local-Global Structural Information for Knowledge Graph Embedding.
- Connecting Embeddings for Knowledge Graph Entity Typing.
- Low-Dimensional Hyperbolic Knowledge Graph Embeddings.
