CIKM2022推荐系统论文集锦

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第31届信息和知识管理国际会议CIKM2022将于2022年10月17日-21日以混合会议的方式在美国亚特兰大举行。CIKM会议是数据库／数据挖掘／内容检索领域顶级国际会议，也是中国计算机学会规定的CCF B类会议。关于该会议在历年推荐系统论文收录情况请参考下文：

CIKM2021推荐系统论文集锦

CIKM2020推荐系统论文集合

本文主要是从教程以及研究型论文和应用型论文中筛选出与推荐系统有关的论文供大家学习，其中与推荐系统有关的教程1项、研究型论文59项、应用型论文19项。本次论文整理涉及到众多推荐系统领域的子方向，比如对经典协同过滤方法的改造、序列推荐、智能家居推荐、多模态推荐、大规模推荐问题、跨域推荐、基于图的推荐系统、基于隐私保护的推荐、基于强化学习的推荐系统、基于自监督学习的推荐系统等。

Tutorials

本会议带来的教程之一为基于自监督学习的推荐系统，具体标题与作者信息如下。

Self-Supervised Learning for Recommendation

Chao Huang (University of Hong Kong), Lianghao Xia (University of Hong Kong), Xiang Wang (University of Science and Technology of China), Xiangnan He (University of Science and Technology of China) and Dawei Yin (Baidu)

Full Papers

本会议所接收的长文主要是关注对经典协同过滤方法的改造、序列推荐、智能家居推荐、多模态推荐、新闻推荐、基于隐私保护的推荐、基于强化学习的推荐系统、基于自监督学习的推荐系统等等。其中大部分论文都已上传到Arxiv，大家可以自行下载进行阅读，也可以前往每周的论文周报进行查看。

A  Multi-Interest Evolution Story: Applying Psychology in Query-based  Recommendation for Inferring Customer Intention

Accurate  Action Recommendation for Smart Home via Two-Level Encoders and Commonsense  Knowledge

Adapting  Triplet Importance of Implicit Feedback for Personalized Recommendation

AutoMARS:  Searching to Compress Multi-Modality Recommendation Systems

Asymmetrical  Context-aware Modulation for Collaborative Filtering Recommendation

Automatic  Meta-Path Discovery for Effective Graph-Based Recommendation

Beyond  Learning from Next Item: Sequential Recommendation via Personalized Interest  Sustainability

CROLoss:  Towards a Customizable Loss for Retrieval Models in Recommender Systems-CROLoss: 一种推荐系统中检索模型的可定制损失函数

ContrastVAE:  Contrastive Variational AutoEncoder for Sequential Recommendation

Contrastive  Cross-Domain Sequential Recommendation

Contrastive  Learning with Bidirectional Transformers for Sequential Recommendation

Cross-domain  Recommendation via Adversarial Adaptation

DeepVT:  Deep View-Temporal Interaction Network for News Recommendation

Disentangling  Past-Future Modeling in Sequential Recommendation via Dual Networks

Dual-Task  Learning for Multi-Behavior Sequential Recommendation

Dually  Enhanced Propensity Score Estimation in Sequential Recommendation

Evolutionary  Preference Learning via Graph Nested GRU ODE for Session-based Recommendation

Explanation  Guided Contrastive Learning for Sequential Recommendation

FedCDR:  Federated Cross-Domain Recommendation for Privacy-Preserving Rating  Prediction

GBERT:  Pre-training User representations for Ephemeral Group Recommendation

GRP:  A Gumbel-based Rating Prediction Framework for Imbalanced Recommendation

Generative  Adversarial Zero-Shot Learning for Cold-Start News Recommendation

Gromov-Wasserstein  Guided Representation Learning for Cross-Domain Recommendation

Hierarchical  Item Inconsistency Signal learning for Sequence Denoising in Sequential  Recommendation

HySAGE:  A Hybrid Static and Adaptive Graph Embedding Network for Context-Drifting  Recommendations

Improving  Knowledge-aware Recommendation with Multi-level Interactive Contrastive  Learning

KuaiRec:  A Fully-observed Dataset and Insights for Evaluating Recommender Systems

Leveraging  Multiple Types of Domain Knowledge for Safe and Effective Drug Recommendation

MARIO:  Modality-Aware Attention and Modality-Preserving Decoders for Multimedia  Recommendation

Memory  Bank Augmented Long-tail Sequential Recommendation

Multi-Aggregator  Time-Warping Heterogeneous Graph Neural Network for Personalized Micro-video  Recommendation

Multi-level  Contrastive Learning Framework for Sequential Recommendation

Quantifying  and Mitigating Popularity Bias in Conversational Recommender Systems

Rank  List Sensitivity of Recommender Systems to Interaction Perturbations

Representation  Matters When Learning From Biased Feedback in Recommendation

Rethinking  Conversational Recommendations: Is Decision Tree All You Need?

Review-Based  Domain Disentanglement without Duplicate Users or Contexts for Cross-Domain  Recommendation

SVD-GCN:  A Simplified Graph Convolution Paradigm for Recommendation

Spatiotemporal-aware  Session-based Recommendation with Graph Neural Networks

Storage-saving  Transformer for Sequential Recommendations

Target  Interest Distillation for Multi-Interest Recommendation

Task  Publication Time Recommendation in Spatial Crowdsourcing

Temporal  Contrastive Pre-Training for Sequential Recommendation

The  Interaction Graph Auto-encoder Network Based on Topology-aware for  Transferable Recommendation

Tiger:  Transferable Interest Graph Embedding for Domain-Level Zero-Shot  Recommendation

Time  Lag Aware Sequential Recommendation

Towards  Principled User-side Recommender Systems

Two-level  Graph Path Reasoning for Conversational Recommendation with User Realistic  Preference

User  Recommendation in Social Metaverse with VR

Graph  Based Long-Term And Short-Term Interest Model for Click-Through Rate  Prediction

Hierarchically  Fusing Long and Short-Term User Interests for Click-Through Rate Prediction  in Product Search

OptEmbed:  Learning Optimal Embedding Table for Click-through Rate Prediction

Towards  Understanding the Overfitting Phenomenon of Deep Click-Through Rate Models

An  Uncertainty-Aware Imputation Framework for Alleviating the Sparsity Problem  in Collaborative Filtering

Dynamic  Hypergraph Learning for Collaborative Filtering

ITSM-GCN:  Informative Training Sample Mining for Graph Convolution Network-based  Collaborative Filtering

MDGCF:  Multi-Dependency Graph Collaborative Filtering with Neighborhood- and  Homogeneous-level Dependencies

NEST:  Simulating Pandemic-like Events for Collaborative Filtering by Modeling User  Needs Evolution

Explainable  Link Prediction in Knowledge Hypergraphs

Applied Papers

本会议所接收的应用型文章与研究型文章的关注点不同，其主要放在了效率和兼容性、大规模推荐场景、可解释性、多样性以及轻量化等提升用户体验的方面。

A Case  Study in Educational Recommenders:Recommending Music Partitures at Tomplay

A  Relevant and Diverse Retrieval-enhanced Data Augmentation Framework for  Sequential Recommendation

Adaptive  Domain Interest Network for Multi-domain Recommendation

Approximate  Nearest Neighbor Search under Neural Similarity Metric for Large-Scale  Recommendation

Improving  Text-based Similar Product Recommendation for Dynamic Product Advertising at  Yahoo

Knowledge  Enhanced Multi-Interest Network for the Generation of Recommendation  Candidates

Knowledge  Extraction and Plugging for Online Recommendation

MIC:Model-agnostic  Integrated Cross-channel Recommender

Multi-Faceted  Hierarchical Multi-Task Learning for Recommender Systems

Multimodal  Meta-Learning for Cold-Start Sequential Recommendation

PROPN:  Personalized Probabilistic Strategic Parameter Optimization in  Recommendations

PlatoGL:  Effective and Scalable Deep Graph Learning System for Graph-enhanced  Real-Time Recommendation

Real-time  Short Video Recommendation on Mobile Devices

SASNet:  Stage-aware sequential matching for online travel recommendation

Scenario-Adaptive  and Self-Supervised Model for Multi-Scenario Personalized Recommendation

UDM:  A Unified Deep Matching Framework in Recommender Systems

推荐阅读

因果推荐系统前沿进展: 形式化与去偏

RecSys2022 | 当推荐系统遇到量子计算

论文周报 | 推荐系统领域最新研究进展

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