点击二部图相关
1. 2021/01/29 【0】A Graph-based Relevance Matching Model for Ad-hoc Retrieval
1.1 Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval
1.2 Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation
1.3 Deep Graph Structure Learning for Robust Representations: A Survey
1.4
2.2021/08/24 【0】Contrastive Learning of User Behavior Sequence for Context-Aware Document Ranking [搜索意图]
数据集&任务：
贡献：
借鉴：
模型：
代码：
3.2016/SIGIR2016: 【0】Learning Query and Document Relevance from a Web-scale Click Graph. [VPCG]
模型:
4.2020/07/03 【0】MIRA:Leveraging Multi-Intention Co-click Information in Web-scale Document Retrieval using Deep Neural Networks
数据集&任务：
贡献：
借鉴：
模型：
代码：
- SIGIR2021: 【0】Modeling Intent Graph for Search Result Diversification. [搜索意图、多样性建模，腾讯是不是也可以从这种角度出发]
数据集&任务：
贡献：
借鉴：
模型
代码
6.Web Page Ranking using Web Mining Techniques: A comprehensive survey [Web structure mining (WSM)/Web content mining (WCM)/Web Usage Mining (WUM)]
7.【0】Ranking relevance in yahoo search [2016引用147，he xiang nan】https://dl.acm.org/doi/abs/10.1145/2939672.2939677?casa_token=0wRUmsmETZEAAAAA:B7arKSsbtMlAtr9Ri8c1zWmuE6D3vuZD07cmSZUkRY7tXcqHbt-2f_jzHEBXdh2bSp0S2y4_jxVvle0 ]
8.Bine: Bipartite network embedding [2018] *** 引用112 [Gao: Bine: Bipartite network embedding - Google 学术搜索]
8.1 【0】Bipartite graph embedding via mutual information maximization
8.2 Cross-GCN: Enhancing Graph Convolutional Network with k-Order Feature Interactions
8.3 Deep learning on graphs
8.4 Collaborative similarity embedding for recommender systems
8.5 Learning Vertex Representations for Bipartite Networks
8.6 【0】BiANE: Bipartite Attributed Network Embedding [属性优化]
8.6.1 Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks
8.6.2 MVGCN: data integration through multi-view graph convolutional network for predicting links in biomedical bipartite networks
8.6.3 Graph-MVP: Multi-View Prototypical Contrastive Learning for Multiplex Graphs
8.7 Cross-GCN: Enhancing Graph Convolutional Network with k-Order Feature Interactions
- 【0】Neural IR Meets Graph Embedding: A Ranking Model for Product Search
9.1 【0】A Hybrid Framework for Session Context Modeling 【2021】 【A Hybrid Framework for Session Context Modeling | ACM Transactions on Information Systems】
9.2 【0】Pre-training Methods in Information Retrieval 【】
- 【0】Learning Better Representations for Neural Information Retrieval with Graph Information 【Learning Better Representations for Neural Information Retrieval with Graph Information | Proceedings of the 29th ACM International Conference on Information & Knowledge Management】
11. AIRC: Attentive Implicit Relation Recommendation Incorporating Content Information for Bipartite Graphs 【q-d再进行编码 Mathematics | Free Full-Text | AIRC: Attentive Implicit Relation Recommendation Incorporating Content Information for Bipartite Graphs (mdpi.com)】
- 【0】 Incorporating Position Bias into Click-Through Bipartite Graph
13. A Graph-Enhanced Click Model for Web Search
-
【0】Beyond Sessions: Exploiting Hybrid Contextual Information for Web Search 【搜索意图***】
-
【0】A Graph-Enhanced Click Model for Web Search 【SIGIR2021****】
二、
【2016】Learning Query and Document Relevance from a Web-scale Click Graph
【2021/01/29】A Graph-based Relevance Matching Model for Ad-hoc Retrieval
论文
【WWW2021】Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval
论文
【2021/08/24】 Contrastive Learning of User Behavior Sequence for Context-Aware Document Ranking
论文arXiv
【2020/07/03】MIRA: Leveraging Multi-Intention Co-click Information in Web-scale Document Retrieval using Deep Neural Networks
论文arXiv
【SIGIR2021】Modeling Intent Graph for Search Result Diversification
论文
【2018】Bine: Bipartite network embedding
论文
笔记
【WSDM2020】 Bipartite graph embedding via mutual information maximization
论文**
【】 Explicit Semantic Cross Feature Learning via Pre-trained Graph Neural Networks for CTR Prediction
论文
笔记.
【201812】Deep learning on graphs
论文
笔记
【】Learning Vertex Representations for Bipartite Networks
论文
【wsdm2021】Bipartite Graph Embedding via Mutual Information Maximization
论文
【www2021】Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks
论文
【SIGIR2020】BiANE: Bipartite Attributed Network Embedding
论文
【202110】Graph-MVP: Multi-View Prototypical Contrastive Learning for Multiplex Graphs
论文
【WWW2019】Neural IR Meets Graph Embedding: A Ranking Model for Product Search
论文
【2021 liuyiqun】A Hybrid Framework for Session Context Modeling
论文
【20211127 | liuyiqun】Pre-training Methods in Information Retrieval
论文
【2021202】Learning Large-scale Network Embedding from Representative Subgraph
论文
【CIKM2020 | liuyiqun】Learning Better Representations for Neural Information Retrieval with Graph Information
论文
【2020】AIRC: Attentive Implicit Relation Recommendation Incorporating Content Information for Bipartite Graphs
论文
【不推荐】Incorporating Position Bias into Click-Through Bipartite Graph
【SIGIR2021 | 张伟楠】A Graph-Enhanced Click Model for Web Search
论文
【WSDM2020】Beyond Sessions: Exploiting Hybrid Contextual Information for Web Search
论文
【】Web Page Ranking using Web Mining Techniques: A comprehensive survey
【TOIS | 张伟楠】Beyond Relevance Ranking: A General Graph Matching Framework for Utility-Oriented Learning to Rank
论文
三、CTR
【KDD2021 | 张伟楠】An Embedding Learning Framework for Numerical Features in CTR Prediction
论文 特征离散化处理
【CIKM2021】 Enhancing Explicit and Implicit Feature Interactions via Information Sharing for Parallel Deep CTR Models
论文.
【IJCAI2021 | 张伟楠 ｜ 综述】Deep Learning for Click-Through Rate Estimation
论文
【KDD2020 | 张伟楠】| AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction
论文
【SIGIR2020】User Behavior Retrieval for Click-Through Rate Prediction
论文
【2021 | Qingyao Ai】Maximizing Marginal Fairness for Dynamic Learning to Rank
论文
【SIGIR2020】 A Deep Recurrent Survival Model for Unbiased Ranking
论文.
【SIGIR2021】Deep Position-wise Interaction Network for CTR Prediction
论文