CoNet: Collaborative Cross Networks for Cross-Domain Recommendation

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Research Works Comparing CoNet as Baseline

Conferences
  1. Graph Disentangled Contrastive Learning with Personalized Transfer for Cross-Domain Recommendation. Liu et al. AAAI, 2024
  2. 𝐶2𝐷𝑅: Robust Cross-Domain Recommendation based on Causal Disentanglement. Kong et al. WSDM, 2024
  3. DREAM Decoupled Representation via Extraction Attention Module and Supervised Contrastive Learning for Cross-Domain Sequential Recommender. Ye et al. RecSys, 2023
  4. Sequential Recommendation via an Adaptive Cross-domain Knowledge Decomposition. Zhao et al. CIKM, 2023
  5. A Multi-view Graph Contrastive Learning Framework for Cross-Domain Sequential Recommendation. Xu et al. RecSys, 2023
  6. Dual Interests-Aligned Graph Auto-Encoders for Cross-domain Recommendation in WeChat. Zheng et al. CIKM, 2023
  7. Non-IID Transfer Learning on Graphs. Wu et al. AAAI, 2023
  8. Cross-Domain Disentangled Learning for E-Commerce Live Streaming Recommendation. Zhang et al. ICDE, 2023
    CoNet is extended by incorporating sequential information as users' general features.
  9. Connecting Unseen Domains: Cross-Domain Invariant Learning in Recommendation. Zhang et al. SIGIR, 2023
    CoNet is the best baseline in terms of MSE and AUC metrics on both Amazon and Ant Group datasets, and it even outperforms the variant of the newly proposed Grace method.
  10. A Collaborative Transfer Learning Framework for Cross-domain Recommendation. Zhang et al. SIGKDD, 2023
  11. Intra and Inter Domain HyperGraph Convolutional Network for Cross-Domain Recommendation. Han et al. TheWebConf, 2023
  12. PPGenCDR: A Stable and Robust Framework for Privacy-Preserving Cross-Domain Recommendation. Liao et al. AAAI, 2023
  13. Win-Win A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation. Chen et al. AAAI, 2023
  14. Disentangled Contrastive Learning for Cross-Domain Recommendation. Zhang et al. DASFAA, 2023
    CoNet is the best baseline in terms of Hit@5 on Douban-{Book,Music} datasets
  15. Cross-domain Recommendation with Behavioral Importance Perception. Chen et al. TheWebConf, 2023
    CoNet is chosen to be the Base model of the proposed method
  16. Towards Universal Cross-Domain Recommendation. Cao et al. WSDM, 2023
  17. Self-Supervised Interest Transfer Network via Prototypical Contrastive Learning for Recommendation. Sun et al. AAAI, 2023
  18. Contrastive Cross-Domain Sequential Recommendation. Cao et al. CIKM, 2022
  19. Cross-Domain Product Search with Knowledge Graph. Zhu et al. CIKM, 2022
    CoNet is evaluated on Alipay digital finance search platform and shows good performance in terms of NDCG under cold-start test
  20. DDGHM: Dual Dynamic Graph with Hybrid Metric Training for Cross-Domain Sequential Recommendation. Zheng et al. ACM MM, 2022
  21. Cross-Domain Recommendation to Cold-Start Users via Variational Information Bottleneck. Cao et al. ICDE, 2022
    CoNet is the best in terms of HR@1 on Phone-domain rec.
  22. Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation. Chen et al. TheWebConf, 2022
  23. KEEP: An Industrial Pre-Training Framework for Online Recommendation via Knowledge Extraction and Plugging. Zhang et al. CIKM, 2022
    CoNet is trained and evaluated on billions-scale data of Taobao, Alibaba
  24. Multi-Sparse-Domain Collaborative Recommendation via Enhanced Comprehensive Aspect Preference Learning. Zhao et al. WSDM, 2022
  25. DisenCDR: Learning Disentangled Representations for Cross-Domain Recommendation. Cao et al. SIGIR, 2022
  26. DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation. Guo et al. IJCAI, 2021
  27. CMML: Contextual Modulation Meta Learning for Cold-Start Recommendation. Feng et al. RecSys, 2021
  28. Debiasing Learning based Cross-domain Recommendation. Li et al. KDD, 2021
  29. Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate Prediction. Li et al. KDD, 2021
  30. RevMan: Revenue-aware Multi-task Online Insurance Recommendation. Li et al. AAAI, 2021
  31. Learning Personalized Itemset Mapping for Cross-Domain Recommendation. Zhang et al. IJCAI, 2020
  32. DDTCDR: Deep Dual Transfer Cross Domain Recommendation. Li & Tuzhilin. WSDM, 2020
  33. MiNet: Mixed Interest Network for Cross-Domain Click-Through Rate Prediction. Ouyang et al. CIKM, 2020
  34. Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks. Liu et al. CIKM, 2020
  35. Exploiting Aesthetic Preference in Deep Cross Networks for Cross-domain Recommendation. Liu et al. TheWebConf, 2020
  36. Sequential Scenario-Specific Meta Learner for Online Recommendation. Du et al. KDD, 2019
  37. DARec: Deep Domain Adaptation for Cross-Domain Recommendation via Transferring Rating Patterns. Yuan et al. IJCAI, 2019
  38. Cross-Domain Recommendation via Preference Propagation GraphNet. Zhao et al. CIKM, 2019 [PPGN-code]
    SCoNot, the sparse variant of CoNet, is also compared and is better on three out of four datasets.
  39. π-Net: A Parallel Information-sharing Network for Shared-account Cross-domain Sequential Recommendations. Ma et al. SIGIR, 2019
Journals
  1. Inter- and Intra-Domain Potential User Preferences for Cross-Domain Recommendation. Liu et al. IEEE TMM, 2024
  2. A Dual Perspective Framework of Knowledge-correlation for Cross-domain Recommendation. Wang et al. ACM TKDD, 2024
  3. Adaptive Adversarial Contrastive Learning for Cross-Domain Recommendation. Hsu et al. ACM TKDD, 2023
  4. Towards Flexible and Adaptive Neural Process for Cold-Start Recommendation. Liu et al. IEEE TKDE, 2023
    CoNot shows better performance varying with K from 20 to 100 in terms of Recall@K on the Taobao dataset.
  5. Contrastive Graph Prompt-tuning for Cross-domain Recommendation. Yi et al. ACM Trans Info Sys, 2023
    CoNot even outperforms the GNN-based NGCF baseline on two datasets (Elec-Phone and Sport-Cloth).
  6. A VAE-based User Preference Learning and Transfer Framework for Cross-domain Recommendation. Zhang et al. IEEE TKDE, 2023
  7. Cross-Domain Meta-Learner for Cold-Start Recommendation. Guan et al. IEEE TKDE, 2022
    SCoNot, the sparse variant of CoNet, is compared on four scenarios (warm start, user cold, item cold, and user-item cold start
  8. Adversarial Learning for Cross Domain Recommendations. Li et al. ACM TIST, 2022
  9. Towards Equivalent Transformation of User Preferences in Cross Domain Recommendation. Chen et al. ACM TOIS, 2022
  10. Time Interval-enhanced Graph Neural Network for Shared-account Cross-domain Sequential Recommendation. Guo et al. IEEE TNNLS, 2022
  11. Reinforcement Learning-enhanced Shared-account Cross-domain Sequential Recommendation. Guo et al. IEEE TKDE, 2022
  12. Mixed Information Flow for Cross-Domain Sequential Recommendations. Ma et al. ACM TKDD, 2022
  13. Dual Metric Learning for Effective and Efficient Cross-Domain Recommendations. Li & Tuzhilin. IEEE TKDE, 2021
  14. E-Commerce Storytelling Recommendation Using Attentional Domain-Transfer Network and Adversarial Pre-Training. Chen et al. IEEE TMM, 2021
Other J&C, Workshop & Preprint
  1. A Novel Cross-Domain Recommendation with Evolution Learning. Chen & Lee ACM Trans. Internet Technol., 2024
  2. Analyzing the Impact of Domain Similarity A New Perspective in Cross-Domain Recommendation. Vajjala et al. IJCNN, 2024
  3. MeKB-Rec: Personal Knowledge Graph Learning for Cross-Domain Recommendation. Su et al. RecSys workshop, 2023
  4. A Graph Neural Network for Cross-domain Recommendation Based on Transfer and Inter-domain Contrastive Learning. Mu et al. KSEM, 2023
  5. Proxy-Aware Cross-Domain Sequential Recommendation. Xiao et al. IJCNN, 2023
  6. Cross Domain Deep Collaborative Filtering without Overlapping Data. Liu et al. IJCNN, 2023
  7. DADIN: Domain Adversarial Deep Interest Network for Cross Domain Recommender Systems. Kong et al. submitted to Elsevier, 2023
    CoNot has the best Logloss among all 12 models on the Amazon dataset.
  8. Exploring Local Information for Graph Representation Learning. Li Zhang. PhD Thesis, 2022
  9. A Multi-Head Attention Based Dual Target Graph Collaborative Filtering Network. Peng et al. IEEE, 2022
  10. CDAML: a cluster-based domain adaptive meta-learning model for cross domain recommendation. Xu et al. World Wide Web, 2022
  11. Knowledge-aware Neural Collective Matrix Factorization for Cross-domain Recommendation. Zhang et al. KDD Workshop, 2022
  12. Explicitly Modeling Relationships between Domain-Specific and Domain-Invariant Interests for Cross-Domain Recommendation. Zang et al. Under Review at World Wide Web, 2022
  13. Strategies to Solve the Problem of Information Cocoon—Research Progress of Cross-domain Recommendation Algorithm Based on Mining the Potential Interests of Users. Bao & Tu. CONF-SPML, 2022
  14. Pre-training Graph Neural Network for Cross Domain Recommendation. Wang et al. CogMI, 2021
  15. Deep Matrix Factorization for Cross-Domain Recommendation. Kuang et al. IAEAC, 2021
  16. NAUI : Neural Attentive User Interest Model for Cross-Domain CTR Prediction. Wang et al. J. Phys.: Conf. Ser, 2021
  17. Cross-Domain Sequential Recommendation Based on Self-Attention and Transfer Learning. Liu & Zhu. J. Phys.: Conf. Ser, 2021
  18. ATLRec: An Attentional Adversarial Transfer Learning Network for Cross-Domain Recommendation. Li et al. Journal of Comp. Sci. & Tech., 2020
  19. On accurate POI recommendation via transfer learning. Zhang et al. Distributed and Parallel Databases, 2020
  20. RACRec: Review Aware Cross-Domain Recommendation for Fully-Cold-Start User. Jin et al. IEEE Access, 2020
  21. Collaborative Adversarial Learning for Relational Learning on Multiple Bipartite Graphs. Su et al. ICKG, 2020
  22. JSCN: Joint spectral convolutional network for cross domain recommendation. Liu et al. IEEE BigData, 2019 [code]
  23. Neural Attentive Cross-Domain Recommendation. Rafailidis & Crestani. SIGIR on Theory of IR (ICTIR), 2019
    SCoNot, the sparse variant of CoNet, is the best baseline in terms of both Recal & NDCG metrics on all of the ten domains.
  24. Cross-Domain Collaborative Filtering via Translation-based Learning. D. Rafailidis. arXiv, 2019
    SCoNot, the sparse variant of CoNet, is the best baseline on three out of six domains.
  25. Adaptive Deep Learning of Cross-Domain Loss in Collaborative Filtering. Rafailidis & Weiss. arXiv, 2019
  26. Latent User Linking for Collaborative Cross-Domain Recommendation. Ahangama & Poo. arXiv, 2019
  27. Deep Cross Networks with Aesthetic Preference for Cross-domain Recommendation. Liu et al. arXiv, 2019
    Updated version: [TheWebConf'20]

Recommendation Lib Implemented CoNet as Toolkit

  1. RecBole 2.0: Towards a More Up-to-Date Recommendation Library. Zhao et al. arXiv, 2022 [paper]

Datasets for Cross-Domain Rec


Please do not hesitate to inform us of any missing works.

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