| SN | Title | Venue | Year | Code |
| 1 | Exploring the Individuality and Collectivity of Intents behind Interactions for Graph Collaborative Filtering | SIGIR'24 | 2024 | https://github.com/BlueGhostYi/BIGCF |
| 2 | Disentangled Contrastive Collaborative Filtering | SIGIR'24 | 2024 | https://github.com/HKUDS/DCCF |
| 3 | Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation | ICDE 2023 | 2023 | https://arxiv.org/abs/2211.06370 |
| 4 | MISRec: Multi-Intention Sequential Recommendation | Web and Big Data | 2023 | https://link.springer.com/10.1007/978-3-031-25201-3_15 |
| 5 | Developing smart city services using intent‐aware recommendation systems | Trans Emerging Tel Tech | 2023 | https://onlinelibrary.wiley.com/doi/10.1002/ett.4728 |
| 6 | Multi-Intention Oriented Contrastive Learning for Sequential Recommendation | WSDM '23 | 2023 | https://dl.acm.org/doi/10.1145/3539597.3570411 |
| 7 | Entity-driven user intent inference for knowledge graph-based recommendation | Appl Intell | 2023 | https://link.springer.com/10.1007/s10489-022-04048-4 |
| 8 | Intent-Satisfaction Modeling: From Music to Video Streaming | ACM TORS | 2023 | https://dl.acm.org/doi/10.1145/3606375 |
| 9 | Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation | WWW '23 | 2023 | https://dl.acm.org/doi/10.1145/3543507.3583526 |
| 10 | Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network | WSDM '23 | 2023 | https://dl.acm.org/doi/10.1145/3539597.3570445 |
| 11 | Latent User Intent Modeling for Sequential Recommenders | WWW '23 | 2023 | https://dl.acm.org/doi/10.1145/3543873.3584641 |
| 12 | Topic-aware Intention Network for Explainable Recommendation with Knowledge Enhancement | TOIS | 2023 | https://dl.acm.org/doi/10.1145/3579993 |
| 13 | IKGN: Intention-aware Knowledge Graph Network for POI Recommendation | ICDM 2023 | 2023 | https://ieeexplore.ieee.org/document/10415663 |
| 14 | Attention Over Self-Attention: Intention-Aware Re-Ranking With Dynamic Transformer Encoders for Recommendation | TKDE | 2023 | https://www.computer.org/csdl/journal/tk/2023/08/09906456/1H5EKIMPrK8 |
| 15 | A Knowledge Graph Recommendation Model via High-order Feature Interaction and Intent Decomposition | IJCNN '22 | 2022 | https://ieeexplore.ieee.org/document/9892593/ |
| 16 | A multi-intent based multi-policy relay contrastive learning for sequential recommendation | PeerJ Computer Science | 2022 | https://peerj.com/articles/cs-1088 |
| 17 | Causal Disentanglement for Semantics-Aware Intent Learning in Recommendation | IEEE Trans. Knowl. Data Eng. | 2022 | https://ieeexplore.ieee.org/document/9736612/ |
| 18 | Multi-View Intent Disentangle Graph Networks for Bundle Recommendation | AAAI '22 | 2022 | https://ojs.aaai.org/index.php/AAAI/article/view/20359 |
| 19 | Learning aspect-level complementarity for intent-aware complementary recommendation | Knowledge-Based Systems | 2022 | https://linkinghub.elsevier.com/retrieve/pii/S0950705122010292 |
| 20 | Dynamic intent-aware iterative denoising network for session-based recommendation | IP&M | 2022 | https://linkinghub.elsevier.com/retrieve/pii/S0306457322000590 |
| 21 | Enhancing Hypergraph Neural Networks with Intent Disentanglement for Session-based Recommendation | SIGIR '22 | 2022 | https://dl.acm.org/doi/10.1145/3477495.3531794 |
| 22 | FIRE: knowledge-enhanced recommendation with feature interaction and intent-aware attention networks | Applied Intelligence | 2022 | https://link.springer.com/10.1007/s10489-022-04300-x |
| 23 | From Data Analysis to Intent-Based Recommendation | IEEE Access | 2022 | https://ieeexplore.ieee.org/document/9701319/ |
| 24 | Intent Disentanglement and Feature Self-supervision for Novel Recommendation | TKDE | 2022 | http://arxiv.org/abs/2106.14388 |
| 25 | Intent Contrastive Learning for Sequential Recommendation | WWW '22 | 2022 | https://arxiv.org/abs/2202.02519 |
| 26 | Intention-Aware Sequential Recommendation With Structured Intent Transition | TKDE | 2022 | https://ieeexplore.ieee.org/document/9319534/ |
| 27 | Learning Multi-granularity Consecutive User Intent Unit for Session-based Recommendation | WSDM '22 | 2022 | https://dl.acm.org/doi/10.1145/3488560.3498524 |
| 28 | Making smartphone service recommendations by predicting users’ intentions | Information Sciences | 2022 | https://linkinghub.elsevier.com/retrieve/pii/S0020025514004873 |
| 29 | Modeling Instant User Intent and Content-Level Transition for Sequential Fashion Recommendation | IEEE Trans. Multimedia | 2022 | https://ieeexplore.ieee.org/document/9451610/ |
| 30 | Multi-intent Compatible Transformer Network for Recommendation | Pattern Recognition and Computer Vision | 2022 | https://link.springer.com/10.1007/978-3-031-18907-4_27 |
| 31 | Hierarchical User Intent Graph Network for Multimedia Recommendation | IEEE Transactions on Multimedia | 2022 | https://ieeexplore.ieee.org/document/9453189/ |
| 32 | Learning a Hierarchical Intent Model for Next-Item Recommendation | ACM Trans. Inf. Syst. | 2022 | https://dl.acm.org/doi/10.1145/3473972 |
| 33 | Sequential Intention-aware Recommender based on User Interaction Graph | ICMR '22: International Conference on Multimedia Retrieval | 2022 | https://dl.acm.org/doi/10.1145/3512527.3531390 |
| 34 | Target Interest Distillation for Multi-Interest Recommendation | CIKM '22 | 2022 | https://dl.acm.org/doi/10.1145/3511808.3557464 |
| 35 | Implicit Session Contexts for Next-Item Recommendations | CIKM '22 | 2022 | https://dl.acm.org/doi/10.1145/3511808.3557613 |
| 36 | Spatiotemporal-aware Session-based Recommendation with Graph Neural Networks | CIKM '22 | 2022 | https://dl.acm.org/doi/10.1145/3511808.3557458 |
| 37 | Automatically Discovering User Consumption Intents in Meituan | KDD 22 | 2022 | https://dl.acm.org/doi/abs/10.1145/3534678.3539122 |
| 38 | FINN: Feedback Interactive Neural Network for Intent Recommendation | WWW '21 | 2021 | https://dl.acm.org/doi/10.1145/3442381.3450105 |
| 39 | Package Recommendation with Intra- and Inter-Package Attention Networks | SIGIR '21 | 2021 | https://dl.acm.org/doi/10.1145/3404835.3462841 |
| 40 | Learning Intents behind Interactions with Knowledge Graph for Recommendation | WWW '21 | 2021 | https://dl.acm.org/doi/10.1145/3442381.3450133 |
| 41 | Sparse-Interest Network for Sequential Recommendation | WSDM '21 | 2021 | http://arxiv.org/abs/2102.09267 |
| 42 | Toward Dynamic User Intention: Temporal Evolutionary Effects of Item Relations in Sequential Recommendation | ACM TOIS | 2021 | https://dl.acm.org/doi/10.1145/3432244 |
| 43 | Category-aware Collaborative Sequential Recommendation | SIGIR '21 | 2021 | https://dl.acm.org/doi/10.1145/3404835.3462832 |
| 44 | Dynamic Sequential Recommendation: Decoupling User Intent from Temporal Context | International Conference on Data Mining Workshops (ICDMW) | 2021 | https://ieeexplore.ieee.org/document/9679889/ |
| 45 | Modeling Multiple Coexisting Category-Level Intentions for Next Item Recommendation | ACM Trans. Inf. Syst. | 2021 | https://dl.acm.org/doi/10.1145/3441642 |
| 46 | An Intent-guided Collaborative Machine for Session-based Recommendation | SIGIR '20 | 2020 | https://dl.acm.org/doi/10.1145/3397271.3401273 |
| 47 | Attentive Sequential Models of Latent Intent for Next Item Recommendation | WWW '20 | 2020 | https://dl.acm.org/doi/10.1145/3366423.3380002 |
| 48 | Basket Recommendation with Multi-Intent Translation Graph Neural Network | BigData '20 | 2020 | https://ieeexplore.ieee.org/document/9377917/ |
| 49 | Intention2Basket: A Neural Intention-driven Approach for Dynamic Next-basket Planning | IJCAI '20 | 2020 | https://www.ijcai.org/proceedings/2020/323 |
| 50 | Disentangled Graph Collaborative Filtering | SIGIR '20 | 2020 | https://dl.acm.org/doi/10.1145/3397271.3401137 |
| 51 | Intention Nets: Psychology-Inspired User Choice Behavior Modeling for Next-Basket Prediction | AAAI '20 | 2020 | https://ojs.aaai.org/index.php/AAAI/article/view/6093 |
| 52 | Improving End-to-End Sequential Recommendations with Intent-aware Diversification | CIKM '20 | 2020 | https://dl.acm.org/doi/10.1145/3340531.3411897 |
| 53 | Time-Sensitive Collaborative Interest Aware Model for Session-Based Recommendation | ICME '20 | 2020 | https://ieeexplore.ieee.org/document/9102915/ |
| 54 | Intention Modeling from Ordered and Unordered Facets for Sequential Recommendation | WWW '20 | 2020 | https://dl.acm.org/doi/10.1145/3366423.3380190 |
| 55 | Octopus: Comprehensive and Elastic User Representation for the Generation of Recommendation Candidates | SIGIR '20 | 2020 | https://dl.acm.org/doi/10.1145/3397271.3401088 |
| 56 | DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation | CIKM '20 | 2020 | https://dl.acm.org/doi/10.1145/3340531.3411996 |
| 57 | Sequential Modeling of Hierarchical User Intention and Preference for Next-item Recommendation | WSDM '20 | 2020 | https://dl.acm.org/doi/10.1145/3336191.3371840 |
| 58 | Graph Neural News Recommendation with Unsupervised Preference Disentanglement | ACL '20 | 2020 | https://www.aclweb.org/anthology/2020.acl-main.392 |
| 59 | TPGN: A Time-Preference Gate Network for e-commerce purchase intention recognition | Knowledge-Based Systems | 2020 | https://linkinghub.elsevier.com/retrieve/pii/S0950705121001830 |
| 60 | Controllable Multi-Interest Framework for Recommendation | KDD '20 | 2020 | https://dl.acm.org/doi/10.1145/3394486.3403344 |
| 61 | Disentangled Self-Supervision in Sequential Recommenders | KDD '20 | 2020 | https://dl.acm.org/doi/10.1145/3394486.3403091 |
| 62 | Intent Preference Decoupling for User Representation on Online Recommender System | IJCAI '20 | 2020 | https://www.ijcai.org/proceedings/2020/357 |
| 63 | A comparison of calibrated and intent-aware recommendations | RecSys '19 | 2019 | https://dl.acm.org/doi/10.1145/3298689.3347045 |
| 64 | AIR: Attentional Intention-Aware Recommender Systems | ICDE 2019 | 2019 | https://ieeexplore.ieee.org/document/8731605/ |
| 65 | Jointly Leveraging Intent and Interaction Signals to Predict User Satisfaction with Slate Recommendations | WWW '19 |
2019 | https://dl.acm.org/doi/10.1145/3308558.3313613 |
| 66 | Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation | KDD '19 | 2019 | https://dl.acm.org/doi/10.1145/3292500.3330673 |
| 67 | How Intention Informed Recommendations Modulate Choices | WWW '19 | 2019 | https://dl.acm.org/doi/10.1145/3308558.3313540 |
| 68 | Next Item Recommendation with Self-Attentive Metric Learning | RecNLP Workshop 2019 | 2019 | https://recnlp2019.github.io/papers/RecNLP2019_paper_21.pdf |
| 69 | Learning Disentangled Representations for Recommendation | NeurIPS '19 | 2019 | https://dl.acm.org/doi/10.5555/3454287.3454800 |
| 70 | Multi-Interest Network with Dynamic Routing for Recommendation at Tmall | CIKM '19 | 2019 | https://dl.acm.org/doi/10.1145/3357384.3357814 |
| 71 | Modeling Multi-Purpose Sessions for Next-Item Recommendations via Mixture-Channel Purpose Routing Networks | IJCAI '19 | 2019 | https://www.ijcai.org/proceedings/2019/523 |
| 72 | On-Device User Intent Prediction for Context and Sequence Aware Recommendation | Preprint, CARS 2019 | 2019 | http://arxiv.org/abs/1909.12756 |
| 73 | A Collaborative Session-based Recommendation Approach with Parallel Memory Modules | SIGIR 19 | 2019 | https://dl.acm.org/doi/10.1145/3331184.3331210 |
| 74 | Accurate and Diverse Recommendations Using Item-Based SubProfile | FLAIRS 2018 | 2018 | https://cdn.aaai.org/ocs/17600/17600-77648-1-PB.pdf |
| 75 | An Attention-Based Recommender System to Predict Contextual Intent Based on Choice Histories across and within Sessions | Applied Sciences (MDPI) | 2018 | http://www.mdpi.com/2076-3417/8/12/2426 |
| 76 | Towards Intent-Aware Contextual Music Recommendation: Initial Experiments | SIGIR '18 | 2018 | https://dl.acm.org/doi/10.1145/3209978.3210154 |
| 77 | STAMP: Short-Term Attention/Memory Priority Model for Session-based Recommendation | KDD '18 | 2018 | https://dl.acm.org/doi/10.1145/3219819.3219950 |
| 78 | Session-based item recommendation in e-commerce: on short-term intents, reminders, trends and discounts | UMUAI | 2017 | http://link.springer.com/10.1007/s11257-017-9194-1 |
| 79 | Improving recommender systems with an intention-based algorithm switching strategy | SAC '17 | 2017 | https://dl.acm.org/doi/10.1145/3019612.3019761 |
| 80 | Modeling User Session and Intent with an Attention-based Encoder-Decoder Architecture | RecSys '17 | 2017 | https://dl.acm.org/doi/10.1145/3109859.3109917 |
| 81 | Neural Attentive Session-based Recommendation | CIKM '17 | 2017 | https://dl.acm.org/doi/10.1145/3132847.3132926 |
| 82 | Intent-Aware Contextual Recommendation System | ICDMW '17 | 2017 | http://ieeexplore.ieee.org/document/8215638/ |
| 83 | Fuzzy Approach to Purchase Intent Modeling Based on User Tracking For E-commerce Recommenders | FUZZ-IEEE '21 | 2017 | https://ieeexplore.ieee.org/document/9494585 |
| 84 | Intent-Aware Diversification Using a Constrained PLSA | RecSys '16 | 2016 | https://dl.acm.org/doi/10.1145/2959100.2959177 |
| 85 | I like to explore sometimes: Adapting to Dynamic User Novelty Preferences | RecSys '15 | 2015 | https://dl.acm.org/doi/10.1145/2792838.2800172 |
| 86 | Exploiting regression trees as user models for intent-aware multi-attribute diversity | CBRecSys Workshop | 2015 | https://www.researchgate.net/publication/283473363_Exploiting_regression_trees_as_user_models_for_intent-aware_multi-attribute_diversity |
| 87 | Intent-based recommendation for B2C e-commerce platforms | IBM J. Res. & Dev. | 2014 | https://ieeexplore.ieee.org/abstract/document/6964871 |
| 88 | Towards Intention, Contextual and Social Based Recommender System | Advanced Approaches to Intelligent Information and Database Systems, 2014 | 2014 | https://link.springer.com/10.1007/978-3-319-05503-9_1 |
| 88 | Attention Over Self-Attention: Intention-Aware Re-Ranking With Dynamic Transformer Encoders for Recommendation | TKDE 2023 | 2023 | https://dl.acm.org/doi/10.1109/TKDE.2022.3208633 |