SIGIR 2022 | 推荐系统相关论文分类整理（三）

3.按照研究话题划分

3.1 Bias/Debias in Recommender System

1. Interpolative Distillation for Unifying Biased and Debiased Recommendation

2. Co-training Disentangled Domain Adaptation Network for Leveraging Popularity Bias in Recommenders 【训练解耦的域适应网络来利用流行度偏差】

3. Bilateral Self-unbiased Recommender Learning from Biased Implicit Feedback 【双边去偏】

4. Mitigating Consumer Biases in Recommendations with Adversarial Training 【short paper，对抗训练去偏】

5. Neutralizing Popularity Bias in Recommendation Models 【short paper，中和流行度偏差】

6. DeSCoVeR: Debiased Semantic Context Prior for Venue Recommendation 【short paper，在场所推荐中去除语义上下文先验】

3.2 Explanation in Recommender System

1. Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations 【使用知识图谱为推荐生成崭新的、多样的解释】

2. PEVAE: A hierarchical VAE for personalized explainable recommendation. 【利用层次化VAE进行个性化可解释推荐】

3. Explainable Session-based Recommendation with Meta-Path Guided Instances and Self-Attention Mechanism 【short paper， 基于元路径指导和自注意力机制的可解释会话推荐】

3.3 Long-tail/Cold-start in Recommender System

1. Socially-aware Dual Contrastive Learning for Cold-Start Recommendation 【short paper，社交感知的双重对比学习】

2. Transform Cold-Start Users into Warm via Fused Behaviors in Large-Scale Recommendation 【short paper，通过融合行为转换冷启动用户】

3. Generative Adversarial Framework for Cold-Start Item Recommendation 【short paper，针对冷启动商品的生成对抗框架】

4. Improving Item Cold-start Recommendation via Model-agnostic Conditional Variational Autoencoder 【short paper，模型无关的自编码器提升商品冷启动推荐】

3.4 Fairness in Recommender System

1. Joint Multisided Exposure Fairness for Recommendation 【综合考虑多边的曝光公平性】

2. ProFairRec: Provider Fairness-aware News Recommendation 【商家公平的新闻推荐】

3. CPFair: Personalized Consumer and Producer Fairness Re-ranking for Recommender Systems 【用户和商家公平的重排序】

4. Explainable Fairness for Feature-aware Recommender Systems 【考虑特征的推荐系统中的可解释公平】

5. Selective Fairness in Recommendation via Prompts 【short paper，通过提示保证可选的公平性】

6. Regulating Provider Groups Exposure in Recommendations 【short paper，调整商家组曝光】

3.5 Diversity in Recommender System

1. DAWAR: Diversity-aware Web APIs Recommendation for Mashup Creation based on Correlation Graph 【多样化Web API推荐】

2. Mitigating the Filter Bubble while Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems 【short paper，定向多样化】

3. Diversity vs Relevance: a practical multi-objective study in luxury fashion recommendations 【short paper，奢侈品推荐中的多目标研究】

3.6 Attack/Denoise in Recommender System

1. Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering 【数据去噪】

2. Less is More: Reweighting Important Spectral Graph Features for Recommendation 【评估重要的图谱特征】

3. Denoising Time Cycle Modeling for Recommendation 【short paper，去噪时间循环建模】

4. Adversarial Graph Perturbations for Recommendations at Scale 【short paper，大规模推荐中的对抗图扰动】

3.7Others

1. Privacy-Preserving Synthetic Data Generation for Recommendation 【隐私保护的仿真数据生成】

2. User-Aware Multi-Interest Learning for Candidate Matching in Recommenders 【使用用户多兴趣学习进行候选匹配】

3. User-controllable Recommendation Against Filter Bubbles 【用户可控的推荐】

4. Rethinking Correlation-based Item-Item Similarities for Recommender Systems 【short paper，反思基于关系的商品相似度】

5. ReLoop: A Self-Correction Learning Loop for Recommender Systems 【short paper，推荐系统中的自修正循环学习】

6. Towards Results-level Proportionality for Multi-objective Recommender Systems 【short paper，结果均衡的多目标推荐系统】

4.其他研究方向

4.1 QA

DGQAN: Dual Graph Question-Answer Attention Networks for Answer Selection 【双图注意力网络】

1. Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion 【反事实学习】

2. PTAU: Prompt Tuning for Attributing Unanswerable Questions 【提示微调】

3. Conversational Question Answering on Heterogeneous Sources 【异质来源的问答】

4. A Non-Factoid Question-Answering Taxonomy

5. QUASER: Question Answering with Scalable Extractive Rationalization

6. Detecting Frozen Phrases in Open-Domain Question Answering 【short paper 在开放域问答中检测固定短语】

7. Answering Count Query with Explanatory Evidence 【short paper】

4.1 Knowledge Graph

1. Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion 【多模态知识图谱补全】

2. Incorporating Context Graph with Logical Reasoning for Inductive Relation Prediction 【合并上下文图和逻辑推理进行归纳式关系预测】

3. Meta-Knowledge Transfer for Inductive Knowledge Graph Embedding【元知识迁移解决归纳式知识图谱嵌入】

4. Re-thinking Knowledge Graph Completion Evaluation from an Information Retrieval Perspective 【从信息检索视角思考知识图谱补全的评测】

5. Relation-Guided Few-Shot Relational Triple Extraction 【short paper，关系指导的few-shot三元组抽取】

4.2 Conversation/ Dialog

1. Unified Dialog Model Pre-training for Task-Oriented Dialog Understanding and Generation 【统一对话理解和生成的预训练模型】

2. Interacting with Non-Cooperative User: A New Paradigm for Proactive Dialogue Policy 【主动对话策略的新范式】

3. COSPLAY: Concept Set Guided Personalized Dialogue System 【概念集合指导的个性化对话系统】

4. Understanding User Satisfaction with Task-Oriented Dialogue Systems 【理解用户满意度】

5. A Multi-Task Based Neural Model to Simulate Users in Goal Oriented Dialogue Systems 【short paper 多任务模型仿真用户】

6. Task-Oriented Dialogue System as Natural Language Generation 【short paper，自然语言生成的对话系统】

4.3 Summarization

1. HTKG: Deep Keyphrase Generation with Neural Hierarchical Topic Guidance

2. V2P: Vision-to-Prompt based Multi-Modal Product Summary Generation

3. Unifying Cross-lingual Summarization and Machine Translation with Compression Rate 【使用压缩率统一跨语言总结和机器翻译】

4. ADPL: Adversarial Prompt-based Domain Adaptation for Dialogue Summarization with Knowledge Disentanglement 【基于提示的对抗领域自适应】

5. Summarizing Legal Regulatory Documents using Transformers 【short ，使用Transformers总结法律监管文档】

6. QSG Transformer: Transformer with Query-Attentive Semantic Graph for Query-Focused Summarization 【short paper】

7. MuchSUM: Multi-channel Graph Neural Network for Extractive Summarization 【short paper，多通道图神经网络】

8. Lightweight Meta-Learning for Low-Resource Abstractive Summarization 【short paper， 轻量级元学习】

9. Extractive Elementary Discourse Units for Improving Abstractive Summarization 【short paper】

4.4 Multi-Modality

Tag-assisted Multimodal Sentiment Analysis under Uncertain Missing Modalities

1. Progressive Learning for Image Retrieval with Hybrid-Modality Queries

2. CenterCLIP: Token Clustering for Efficient Text-Video Retrieval

3. Multimodal Entity Linking with Gated Hierarchical Fusion and Contrastive Training

4. CRET: Cross-Modal Retrieval Transformer for Efficient Text-Video Retrieval

5. Bit-aware Semantic Transformer Hashing for Multi-modal Retrieval

6. Video Moment Retrieval from Text Queries via Single Frame Annotation

7. Multimodal Disentanglement Variational AutoEncoders for Zero-Shot Cross-Modal Retrieval

8. A Multitask Framework for Sentiment, Emotion and Sarcasm aware Cyberbullying Detection in Multi-modal Code-Mixed Memes

9. Animating Images to transfer CLIP for Video-Text Retrieval 【short paper， 使用CLIP进行视频-文本检索】

10. Image-Text Retrieval via Contrastive Learning with Auxiliary Generative Features and Support-set Regularization 【short paper】

11. An Efficient Fusion Mechanism for Multimodal Low-resource Setting 【short paper，在低资源下的一种高效融合机制】

4.5 Generation

1. Mutual Disentanglement Learning for Joint Fine-Grained Sentiment Classification and Controllable Text Generation

2. Target-aware Abstractive Related Work Generation with Contrastive Learning 【利用对比学习生成生成相关工作】

3. Generating Clarifying Questions with Web Search Results 【利用Web搜索结果生成清晰问题】

4. Choosing The Right Teammate For Cooperative Text Generation 【short paper 】

4.6 Representation Learning

1. Structure and Semantics Preserving Document Representations 【保留结构和语义的文档表示】

2. Unsupervised Belief Representation Learning with Information-Theoretic Variational Graph Auto-Encoders