Awesome Recommendation Graphs

Privacy Preserving Recommender Systems Balancing Personalization with Privacy (2026)

Ranjeet K Jha et al.

4.95

Can We Steer the Black-Box? Towards Controllability-Centric Evaluation of Recommender Systems with Collaborative Agents (2026)

Jiwen Zhou et al.

4.95

Groc-PO: Grounded Context Preference Optimization for Truthful Multimodal LLMs (2026)

Zhixiao Zheng et al.

4.33

Efficient Recommendations via Graph Coarsening and Label Propagation (2026)

Alessandro Sbandi et al.

4.33

Navigating User Behavior toward Personalized Multimodal Generation (2026)

Hengji Zhou et al.

4.27

Large language models create an uneven informational layer over cities (2026)

Lin Chen et al.

3.45

The User Asks, Platforms Compete: How Agentic Recommendation Markets Take Shape (2026)

Deyao Hong et al.

3.45

Adaptive Structural Similarity Guided GCN–GAT Framework for Robust Link Prediction (2026)

Shambhu Kumar et al.

1.89

GAT-GCN: Drug Molecular Solubility Prediction Based on Graph Neural Networks (2026)

Yiyue Hu

1.89

Song Recommendation with Non-Negative Matrix Factorization and Graph Total Variation (2016)

Kirell Benzi et al.

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Playing the role of weak clique property in link prediction: A friend recommendation model (2016)

Chuang Ma et al.

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GitHub open source project recommendation system (2016)

Tadej Matek et al.

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Embedding Graphs in Lorentzian Spacetime (2016)

James R. Clough and Tim S. Evans

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Compressing Graphs and Indexes with Recursive Graph Bisection (2016)

Laxman Dhulipala and Igor Kabiljo and Brian Karrer and Giuseppe Ottaviano and Sergey Pupyrev and Alon Shalita

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Personalized and situation-aware multimodal route recommendations: the FAVOUR algorithm (2016)

Paolo Campigotto et al.

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Learning Optimal Social Dependency for Recommendation (2016)

Yong Liu et al.

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HARRISON: A Benchmark on HAshtag Recommendation for Real-world Images in Social Networks (2016)

Minseok Park et al.

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Modelling Requirements for Content Recommendation Systems (2016)

Sarah Bouraga and Ivan Jureta and St\'ephane Faulkner

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GT-SEER: Geo-Temporal SEquential Embedding Rank for Point-of-interest Recommendation (2016)

Shenglin Zhao et al.

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Revealing Hidden Connections in Recommendation Networks (2016)

Rogerio Minhano et al.

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Neural Network Based Next-Song Recommendation (2016)

Kai-Chun Hsu et al.

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Application of Statistical Relational Learning to Hybrid Recommendation Systems (2016)

Shuo Yang et al.

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Top-N Recommendation on Graphs (2016)

Zhao Kang et al.

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Formulas for Counting the Sizes of Markov Equivalence Classes of Directed Acyclic Graphs (2016)

Yangbo He and Bin Yu

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Leveraging tagging and rating for recommendation: RMF meets weighted diffusion on tripartite graphs (2016)

Jianguo Li et al.

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Bipolar Weighted Argumentation Graphs (2016)

Till Mossakowski and Fabian Neuhaus

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Distributed Gaussian Learning over Time-varying Directed Graphs (2016)

Angelia Nedi\'c et al.

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On Spectral Analysis of Directed Signed Graphs (2016)

Yuemeng Li et al.

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Evolution of Ego-networks in Social Media with Link Recommendations (2017)

Luca Maria Aiello et al.

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Deep Learning with Dynamic Computation Graphs (2017)

Moshe Looks et al.

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Distributed Representation of Subgraphs (2017)

Bijaya Adhikari et al.

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Weighted Random Walk Sampling for Multi-Relational Recommendation (2017)

Fatemeh Vahedian et al.

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Supervised Typing of Big Graphs using Semantic Embeddings (2017)

Mayank Kejriwal et al.

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Learning Spatiotemporal-Aware Representation for POI Recommendation (2017)

Bei Liu et al.

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The topological face of recommendation: models and application to bias detection (2017)

Erwan Le Merrer and Gilles Tr\'edan

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Permutation Tests for Infection Graphs (2017)

Justin Khim and Po-Ling Loh

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Towards Psychometrics-based Friend Recommendations in Social Networking Services (2017)

Felix Beierle et al.

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Inductive Representation Learning on Large Graphs (2017)

William L. Hamilton et al.

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Graph Based Recommendations: From Data Representation to Feature Extraction and Application (2017)

Amit Tiroshi et al.

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graph2vec: Learning Distributed Representations of Graphs (2017)

Annamalai Narayanan et al.

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PDD Graph: Bridging Electronic Medical Records and Biomedical Knowledge Graphs via Entity Linking (2017)

Meng Wang et al.

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Interacting Attention-gated Recurrent Networks for Recommendation (2017)

Wenjie Pei et al.

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Representation Learning on Graphs: Methods and Applications (2017)

William L. Hamilton et al.

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SMR: Medical Knowledge Graph Embedding for Safe Medicine Recommendation (2017)

Fang Gong et al.

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An extension of the Moran process using type-specific connection graphs (2017)

Themistoklis Melissourgos et al.

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Heterogeneous Information Network Embedding for Recommendation (2017)

Chuan Shi et al.

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Joint Topic-Semantic-aware Social Recommendation for Online Voting (2017)

Hongwei Wang et al.

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User modeling for point-of-interest recommendations in location-based social networks: the state-of-the-art (2017)

Shudong Liu

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Help Me Find a Job: A Graph-based Approach for Job Recommendation at Scale (2018)

Walid Shalaby et al.

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DKN: Deep Knowledge-Aware Network for News Recommendation (2018)

Hongwei Wang et al.

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MotifNet: a motif-based Graph Convolutional Network for directed graphs (2018)

Federico Monti et al.

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WorldTree: A Corpus of Explanation Graphs for Elementary Science Questions supporting Multi-Hop Inference (2018)

Peter A. Jansen et al.

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Any-k: Anytime Top-k Tree Pattern Retrieval in Labeled Graphs (2018)

Xiaofeng Yang et al.

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Clones in Graphs (2018)

Stephan Doerfel and Tom Hanika and Gerd Stumme

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Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba (2018)

Jizhe Wang et al.

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Interact and Decide: Medley of Sub-Attention Networks for Effective Group Recommendation (2018)

Lucas Vinh Tran et al.

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CoNet: Collaborative Cross Networks for Cross-Domain Recommendation (2018)

Guangneng Hu et al.

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RECS: Robust Graph Embedding Using Connection Subgraphs (2018)

Saba A. Al-Sayouri et al.

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(Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs (2018)

Boaz Barak et al.

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Personalized Next Point-of-Interest Recommendation via Latent Behavior Patterns Inference (2018)

Jing He et al.

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Awesome Recommendation Graphs

Datasets & benchmarks

Key papers

Recommendation Graphs

Awesome Recommendation Graphs

Datasets & benchmarks

Key papers