CoNet: Collaborative Cross Networks for Cross-Domain Recommendation

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Research Works Comparing CoNet as Baseline

Conferences

CausalCDR: Causal Embedding Learning for Cross-domain Recommendation. Li et al. SDM, 2024
A Unified Framework for Adaptive Representation Enhancement and Inversed Learning in Cross-Domain Recommendation. Zhang et al. DASFAA, 2024
Graph Disentangled Contrastive Learning with Personalized Transfer for Cross-Domain Recommendation. Liu et al. AAAI, 2024
𝐶2𝐷𝑅: Robust Cross-Domain Recommendation based on Causal Disentanglement. Kong et al. WSDM, 2024
DREAM Decoupled Representation via Extraction Attention Module and Supervised Contrastive Learning for Cross-Domain Sequential Recommender. Ye et al. RecSys, 2023
Sequential Recommendation via an Adaptive Cross-domain Knowledge Decomposition. Zhao et al. CIKM, 2023
A Multi-view Graph Contrastive Learning Framework for Cross-Domain Sequential Recommendation. Xu et al. RecSys, 2023
Dual Interests-Aligned Graph Auto-Encoders for Cross-domain Recommendation in WeChat. Zheng et al. CIKM, 2023
Non-IID Transfer Learning on Graphs. Wu et al. AAAI, 2023
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.
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.
A Collaborative Transfer Learning Framework for Cross-domain Recommendation. Zhang et al. SIGKDD, 2023
Intra and Inter Domain HyperGraph Convolutional Network for Cross-Domain Recommendation. Han et al. TheWebConf, 2023
PPGenCDR: A Stable and Robust Framework for Privacy-Preserving Cross-Domain Recommendation. Liao et al. AAAI, 2023
Win-Win A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation. Chen et al. AAAI, 2023
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
Cross-domain Recommendation with Behavioral Importance Perception. Chen et al. TheWebConf, 2023
CoNet is chosen to be the Base model of the proposed method
Towards Universal Cross-Domain Recommendation. Cao et al. WSDM, 2023
Self-Supervised Interest Transfer Network via Prototypical Contrastive Learning for Recommendation. Sun et al. AAAI, 2023
Contrastive Cross-Domain Sequential Recommendation. Cao et al. CIKM, 2022
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
DDGHM: Dual Dynamic Graph with Hybrid Metric Training for Cross-Domain Sequential Recommendation. Zheng et al. ACM MM, 2022
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.
Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation. Chen et al. TheWebConf, 2022
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
Multi-Sparse-Domain Collaborative Recommendation via Enhanced Comprehensive Aspect Preference Learning. Zhao et al. WSDM, 2022
DisenCDR: Learning Disentangled Representations for Cross-Domain Recommendation. Cao et al. SIGIR, 2022
DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation. Guo et al. IJCAI, 2021
CMML: Contextual Modulation Meta Learning for Cold-Start Recommendation. Feng et al. RecSys, 2021
Debiasing Learning based Cross-domain Recommendation. Li et al. KDD, 2021
Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate Prediction. Li et al. KDD, 2021
RevMan: Revenue-aware Multi-task Online Insurance Recommendation. Li et al. AAAI, 2021
Learning Personalized Itemset Mapping for Cross-Domain Recommendation. Zhang et al. IJCAI, 2020
DDTCDR: Deep Dual Transfer Cross Domain Recommendation. Li & Tuzhilin. WSDM, 2020
MiNet: Mixed Interest Network for Cross-Domain Click-Through Rate Prediction. Ouyang et al. CIKM, 2020
Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks. Liu et al. CIKM, 2020
Exploiting Aesthetic Preference in Deep Cross Networks for Cross-domain Recommendation. Liu et al. TheWebConf, 2020
Sequential Scenario-Specific Meta Learner for Online Recommendation. Du et al. KDD, 2019
DARec: Deep Domain Adaptation for Cross-Domain Recommendation via Transferring Rating Patterns. Yuan et al. IJCAI, 2019
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.
π-Net: A Parallel Information-sharing Network for Shared-account Cross-domain Sequential Recommendations. Ma et al. SIGIR, 2019

Journals

Decoupled domain-specific and domain-conditional representation learning for cross-domain recommendation. Zhang et al. Information Processing and Management, 2024
Enhancing cross-market recommendations by addressing negative transfer and leveraging item co-occurrences. Hu et al. Information Systems, 2024
Transfer learning in cross-domain sequential recommendation. Xu et al. Information Sciences, 2024
CoNet is the representative of general cross-domain recommendations
Inter- and Intra-Domain Potential User Preferences for Cross-Domain Recommendation. Liu et al. IEEE TMM, 2024
A Dual Perspective Framework of Knowledge-correlation for Cross-domain Recommendation. Wang et al. ACM TKDD, 2024
Adaptive Adversarial Contrastive Learning for Cross-Domain Recommendation. Hsu et al. ACM TKDD, 2023
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.
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).
A VAE-based User Preference Learning and Transfer Framework for Cross-domain Recommendation. Zhang et al. IEEE TKDE, 2023
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
Adversarial Learning for Cross Domain Recommendations. Li et al. ACM TIST, 2022
Towards Equivalent Transformation of User Preferences in Cross Domain Recommendation. Chen et al. ACM TOIS, 2022
Time Interval-enhanced Graph Neural Network for Shared-account Cross-domain Sequential Recommendation. Guo et al. IEEE TNNLS, 2022
Reinforcement Learning-enhanced Shared-account Cross-domain Sequential Recommendation. Guo et al. IEEE TKDE, 2022
Mixed Information Flow for Cross-Domain Sequential Recommendations. Ma et al. ACM TKDD, 2022
Dual Metric Learning for Effective and Efficient Cross-Domain Recommendations. Li & Tuzhilin. IEEE TKDE, 2021
E-Commerce Storytelling Recommendation Using Attentional Domain-Transfer Network and Adversarial Pre-Training. Chen et al. IEEE TMM, 2021

Other J&C, Workshop, & arXiv Preprint

Effective Two-Stage Knowledge Transfer for Multi-Entity Cross-Domain Recommendation. Guan et al arXiv, 2024
Cross-channel Recommendation for Multi-channel Retail. Choi et al arXiv, 2024
Learning Partially Aligned Item Representation for Cross-Domain Sequential Recommendation. Yin et al arXiv, 2024
Finetuning Large Language Model for Personalized Ranking. Bai et al arXiv, 2024
A Novel Cross-Domain Recommendation with Evolution Learning. Chen & Lee ACM Trans. Internet Technol., 2024
Analyzing the Impact of Domain Similarity A New Perspective in Cross-Domain Recommendation. Vajjala et al. IJCNN, 2024
MeKB-Rec: Personal Knowledge Graph Learning for Cross-Domain Recommendation. Su et al. RecSys workshop, 2023
A Graph Neural Network for Cross-domain Recommendation Based on Transfer and Inter-domain Contrastive Learning. Mu et al. KSEM, 2023
Proxy-Aware Cross-Domain Sequential Recommendation. Xiao et al. IJCNN, 2023
Cross Domain Deep Collaborative Filtering without Overlapping Data. Liu et al. IJCNN, 2023
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.
Exploring Local Information for Graph Representation Learning. Li Zhang. PhD Thesis, 2022
A Multi-Head Attention Based Dual Target Graph Collaborative Filtering Network. Peng et al. IEEE, 2022
CDAML: a cluster-based domain adaptive meta-learning model for cross domain recommendation. Xu et al. World Wide Web, 2022
Knowledge-aware Neural Collective Matrix Factorization for Cross-domain Recommendation. Zhang et al. KDD Workshop, 2022
Explicitly Modeling Relationships between Domain-Specific and Domain-Invariant Interests for Cross-Domain Recommendation. Zang et al. Under Review at World Wide Web, 2022
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
Pre-training Graph Neural Network for Cross Domain Recommendation. Wang et al. CogMI, 2021
Deep Matrix Factorization for Cross-Domain Recommendation. Kuang et al. IAEAC, 2021
NAUI : Neural Attentive User Interest Model for Cross-Domain CTR Prediction. Wang et al. J. Phys.: Conf. Ser, 2021
Cross-Domain Sequential Recommendation Based on Self-Attention and Transfer Learning. Liu & Zhu. J. Phys.: Conf. Ser, 2021
ATLRec: An Attentional Adversarial Transfer Learning Network for Cross-Domain Recommendation. Li et al. Journal of Comp. Sci. & Tech., 2020
On accurate POI recommendation via transfer learning. Zhang et al. Distributed and Parallel Databases, 2020
RACRec: Review Aware Cross-Domain Recommendation for Fully-Cold-Start User. Jin et al. IEEE Access, 2020
Collaborative Adversarial Learning for Relational Learning on Multiple Bipartite Graphs. Su et al. ICKG, 2020
JSCN: Joint spectral convolutional network for cross domain recommendation. Liu et al. IEEE BigData, 2019 [code]
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.
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.
Adaptive Deep Learning of Cross-Domain Loss in Collaborative Filtering. Rafailidis & Weiss. arXiv, 2019
Latent User Linking for Collaborative Cross-Domain Recommendation. Ahangama & Poo. arXiv, 2019
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

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.