{"url":"/task/session-based-recommendations","name":"Session-Based Recommendations","slug":"session-based-recommendations","description_markdown":"Recommendation based on a sequence of events. e.g. next item prediction","categories":[{"name":"Graphs","url":"/area/graphs"},{"name":"Knowledge Base","url":"/area/knowledge-base"},{"name":"Miscellaneous","url":"/area/miscellaneous"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":172,"papers_with_code":84,"benchmarks":7,"benchmark_tables_in_archive":7,"benchmark_tables_shown":7,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":3,"subtasks":0,"parent_tasks":1},"benchmarks":[{"leaderboard":"/sota/session-based-recommendations-on-diginetica","slug":"session-based-recommendations-on-diginetica","dataset":"Diginetica","dataset_url":null,"rows_in_archive":13,"metrics":["MRR@20","Hit@20"],"first_row_in_archive_order":{"model":"SR-PredAO+DIDN","paper_title":"SR-PredictAO: Session-based Recommendation with High-Capability Predictor Add-On","paper_url":"/paper/sr-predictao-session-based-recommendation","paper_date":"2023-09-20","arxiv_id":"2309.12218","code_links":[{"title":"rickyskywalker/sr-predictao-official","url":"https://github.com/rickyskywalker/sr-predictao-official"}],"syntology":null}},{"leaderboard":"/sota/session-based-recommendations-on-yoochoose1-1","slug":"session-based-recommendations-on-yoochoose1-1","dataset":"yoochoose1/64","dataset_url":null,"rows_in_archive":11,"metrics":["MRR@20","HR@20","Hit@20"],"first_row_in_archive_order":{"model":"SGNN-HN","paper_title":"Star Graph Neural Networks for Session-based Recommendation","paper_url":"/paper/star-graph-neural-networks-for-session-based","paper_date":"2020-10-19","arxiv_id":null,"code_links":[],"syntology":null}},{"leaderboard":"/sota/session-based-recommendations-on-yoochoose1","slug":"session-based-recommendations-on-yoochoose1","dataset":"yoochoose1","dataset_url":null,"rows_in_archive":4,"metrics":["Precision@20","MRR@20"],"first_row_in_archive_order":{"model":"EMDE MM","paper_title":"An efficient manifold density estimator for all recommendation systems","paper_url":"/paper/an-efficient-manifold-density-estimator-for","paper_date":"2020-06-02","arxiv_id":"2006.01894","code_links":[{"title":"Synerise/booking-challenge","url":"https://github.com/Synerise/booking-challenge"},{"title":"Synerise/kdd-cup-2021","url":"https://github.com/Synerise/kdd-cup-2021"}],"syntology":null}},{"leaderboard":"/sota/session-based-recommendations-on-yoochoose1-4","slug":"session-based-recommendations-on-yoochoose1-4","dataset":"yoochoose1/4","dataset_url":null,"rows_in_archive":4,"metrics":["MRR@20","HR@20","Hit@20"],"first_row_in_archive_order":{"model":"STAR","paper_title":"STAR: A Session-Based Time-Aware Recommender System","paper_url":"/paper/star-a-session-based-time-aware-recommender","paper_date":"2022-11-11","arxiv_id":"2211.06394","code_links":[{"title":"yeganegi-reza/star","url":"https://github.com/yeganegi-reza/star"}],"syntology":null}},{"leaderboard":"/sota/session-based-recommendations-on-last-fm","slug":"session-based-recommendations-on-last-fm","dataset":"Last.FM","dataset_url":null,"rows_in_archive":3,"metrics":["MRR@20","HR@20"],"first_row_in_archive_order":{"model":"PEN4Rec","paper_title":"PEN4Rec: Preference Evolution Networks for Session-based Recommendation","paper_url":"/paper/pen4rec-preference-evolution-networks-for","paper_date":"2021-06-17","arxiv_id":"2106.09306","code_links":[{"title":"zerohd4869/PEN4Rec","url":"https://github.com/zerohd4869/PEN4Rec"}],"syntology":null}},{"leaderboard":"/sota/session-based-recommendations-on-retailrocket","slug":"session-based-recommendations-on-retailrocket","dataset":"Retailrocket","dataset_url":"/dataset/retailrocket","rows_in_archive":2,"metrics":["MRR@20","Hit@20"],"first_row_in_archive_order":{"model":"EMDE MM","paper_title":"An efficient manifold density estimator for all recommendation systems","paper_url":"/paper/an-efficient-manifold-density-estimator-for","paper_date":"2020-06-02","arxiv_id":"2006.01894","code_links":[{"title":"Synerise/booking-challenge","url":"https://github.com/Synerise/booking-challenge"},{"title":"Synerise/kdd-cup-2021","url":"https://github.com/Synerise/kdd-cup-2021"}],"syntology":null}},{"leaderboard":"/sota/session-based-recommendations-on-gowalla","slug":"session-based-recommendations-on-gowalla","dataset":"Gowalla","dataset_url":"/dataset/gowalla","rows_in_archive":1,"metrics":["MRR@20","HR@20"],"first_row_in_archive_order":{"model":"SR-GNN","paper_title":"Session-based Recommendation with Graph Neural Networks","paper_url":"/paper/session-based-recommendation-with-graph","paper_date":"2018-11-01","arxiv_id":"1811.00855","code_links":[{"title":"PaddlePaddle/PaddleRec","url":"https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/gnn/"},{"title":"CRIPAC-DIG/SR-GNN","url":"https://github.com/CRIPAC-DIG/SR-GNN"},{"title":"userbehavioranalysis/SR-GNN_PyTorch-Geometric","url":"https://github.com/userbehavioranalysis/SR-GNN_PyTorch-Geometric"},{"title":"rithinch/session-based-vehicle-recommendations","url":"https://github.com/rithinch/session-based-vehicle-recommendations"},{"title":"DiMarzioRock7/SR-GNN","url":"https://github.com/DiMarzioRock7/SR-GNN"},{"title":"xiaominglalala/Session_based_Recommendation","url":"https://github.com/xiaominglalala/Session_based_Recommendation"},{"title":"hkust-knowcomp/sessioncqa","url":"https://github.com/hkust-knowcomp/sessioncqa"},{"title":"herrbilbo/hse-recsys-project","url":"https://github.com/herrbilbo/hse-recsys-project"}],"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":1}}}],"datasets":[{"url":"/dataset/gowalla","name":"Gowalla","full_name":"Gowalla","num_papers_in_archive":203},{"url":"/dataset/retailrocket","name":"Retailrocket","full_name":"","num_papers_in_archive":2},{"url":"/dataset/otto-recommender-systems-dataset","name":"OTTO Recommender Systems Dataset","full_name":"","num_papers_in_archive":1}],"subtasks":[],"parent_tasks":[{"url":"/task/recommendation-systems","name":"Recommendation Systems"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":30,"of":84,"tagged_in_all":172,"items":[{"url":"/paper/xception-deep-learning-with-depthwise","title":"Xception: Deep Learning with Depthwise Separable Convolutions","date":"2016-10-07","arxiv_id":"1610.02357","repositories_listed":41,"syntology":{"n":15,"n_ran":1,"n_unverified":14,"n_pointer_only":0}},{"url":"/paper/session-based-recommendations-with-recurrent","title":"Session-based Recommendations with Recurrent Neural Networks","date":"2015-11-21","arxiv_id":"1511.06939","repositories_listed":25,"syntology":{"n":15,"n_ran":2,"n_unverified":13,"n_pointer_only":4}},{"url":"/paper/recurrent-neural-networks-with-top-k-gains","title":"Recurrent Neural Networks with Top-k Gains for Session-based Recommendations","date":"2017-06-12","arxiv_id":"1706.03847","repositories_listed":12,"syntology":{"n":1,"n_ran":0,"n_unverified":1,"n_pointer_only":1}},{"url":"/paper/session-based-recommendation-with-graph","title":"Session-based Recommendation with Graph Neural Networks","date":"2018-11-01","arxiv_id":"1811.00855","repositories_listed":8,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":1}},{"url":"/paper/session-aware-linear-item-item-models-for","title":"Session-aware Linear Item-Item Models for Session-based Recommendation","date":"2021-03-30","arxiv_id":"2103.16104","repositories_listed":3,"syntology":null},{"url":"/paper/personalizing-graph-neural-networks-with","title":"Personalized Graph Neural Networks with Attention Mechanism for Session-Aware Recommendation","date":"2019-10-20","arxiv_id":"1910.08887","repositories_listed":3,"syntology":null},{"url":"/paper/news-session-based-recommendations-using-deep","title":"News Session-Based Recommendations using Deep Neural Networks","date":"2018-07-31","arxiv_id":"1808.00076","repositories_listed":3,"syntology":null},{"url":"/paper/evaluation-of-session-based-recommendation","title":"Evaluation of Session-based Recommendation Algorithms","date":"2018-03-26","arxiv_id":"1803.09587","repositories_listed":3,"syntology":null},{"url":"/paper/neural-attentive-session-based-recommendation","title":"Neural Attentive Session-based Recommendation","date":"2017-11-13","arxiv_id":"1711.04725","repositories_listed":3,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":1}},{"url":"/paper/self-supervised-graph-co-training-for-session","title":"Self-Supervised Graph Co-Training for Session-based Recommendation","date":"2021-08-24","arxiv_id":"2108.10560","repositories_listed":2,"syntology":null},{"url":"/paper/global-context-enhanced-graph-neural-networks","title":"Global Context Enhanced Graph Neural Networks for Session-based Recommendation","date":"2021-06-09","arxiv_id":"2106.05081","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_unverified":0,"n_pointer_only":3}},{"url":"/paper/self-supervised-hypergraph-convolutional","title":"Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation","date":"2020-12-12","arxiv_id":"2012.06852","repositories_listed":2,"syntology":{"n":2,"n_ran":2,"n_unverified":0,"n_pointer_only":2}},{"url":"/paper/an-efficient-manifold-density-estimator-for","title":"An efficient manifold density estimator for all recommendation systems","date":"2020-06-02","arxiv_id":"2006.01894","repositories_listed":2,"syntology":null},{"url":"/paper/modeling-personalized-item-frequency","title":"Modeling Personalized Item Frequency Information for Next-basket Recommendation","date":"2020-05-31","arxiv_id":"2006.00556","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_unverified":0,"n_pointer_only":0}},{"url":"/paper/niser-normalized-item-and-session","title":"NISER: Normalized Item and Session Representations to Handle Popularity Bias","date":"2019-09-10","arxiv_id":"1909.04276","repositories_listed":2,"syntology":null},{"url":"/paper/on-the-importance-of-news-content","title":"On the Importance of News Content Representation in Hybrid Neural Session-based Recommender Systems","date":"2019-07-12","arxiv_id":"1907.07629","repositories_listed":2,"syntology":{"n":26,"n_ran":0,"n_unverified":26,"n_pointer_only":0}},{"url":"/paper/190410367","title":"Contextual Hybrid Session-based News Recommendation with Recurrent Neural Networks","date":"2019-04-15","arxiv_id":"1904.10367","repositories_listed":2,"syntology":{"n":13,"n_ran":0,"n_unverified":13,"n_pointer_only":0}},{"url":"/paper/personalizing-session-based-recommendations","title":"Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks","date":"2017-06-13","arxiv_id":"1706.04148","repositories_listed":2,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":0}},{"url":"/paper/hierarchical-intent-guided-optimization-with","title":"Hierarchical Intent-guided Optimization with Pluggable LLM-Driven Semantics for Session-based Recommendation","date":"2025-07-07","arxiv_id":"2507.04623","repositories_listed":1,"syntology":null},{"url":"/paper/rethinking-contrastive-learning-in-session","title":"Rethinking Contrastive Learning in Session-based Recommendation","date":"2025-06-05","arxiv_id":"2506.05044","repositories_listed":1,"syntology":null},{"url":"/paper/linear-item-item-model-with-neural-knowledge","title":"Linear Item-Item Model with Neural Knowledge for Session-based Recommendation","date":"2025-04-21","arxiv_id":"2504.15057","repositories_listed":1,"syntology":null},{"url":"/paper/unsupervised-graph-embeddings-for-session","title":"Unsupervised Graph Embeddings for Session-based Recommendation with Item Features","date":"2025-02-19","arxiv_id":"2502.13763","repositories_listed":1,"syntology":null},{"url":"/paper/spgl-enhancing-session-based-recommendation","title":"SPGL: Enhancing Session-based Recommendation with Single Positive Graph Learning","date":"2024-12-16","arxiv_id":"2412.11846","repositories_listed":1,"syntology":null},{"url":"/paper/multi-graph-co-training-for-capturing-user","title":"Multi-Graph Co-Training for Capturing User Intent in Session-based Recommendation","date":"2024-12-15","arxiv_id":"2412.11105","repositories_listed":1,"syntology":null},{"url":"/paper/enhancing-attributed-graph-networks-with","title":"Enhancing Attributed Graph Networks with Alignment and Uniformity Constraints for Session-based Recommendation","date":"2024-10-14","arxiv_id":"2410.10296","repositories_listed":1,"syntology":null},{"url":"/paper/enhancing-sequential-music-recommendation-1","title":"Enhancing Sequential Music Recommendation with Negative Feedback-informed Contrastive Learning","date":"2024-09-11","arxiv_id":"2409.07367","repositories_listed":1,"syntology":null},{"url":"/paper/multi-intent-aware-session-based","title":"Multi-intent-aware Session-based Recommendation","date":"2024-05-02","arxiv_id":"2405.00986","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_unverified":2,"n_pointer_only":7}},{"url":"/paper/disentangling-id-and-modality-effects-for","title":"Disentangling ID and Modality Effects for Session-based Recommendation","date":"2024-04-19","arxiv_id":"2404.12969","repositories_listed":1,"syntology":null},{"url":"/paper/a-simple-yet-effective-approach-for","title":"A Simple Yet Effective Approach for Diversified Session-Based Recommendation","date":"2024-03-30","arxiv_id":"2404.00261","repositories_listed":1,"syntology":null},{"url":"/paper/llm4sbr-a-lightweight-and-effective-framework","title":"Multi-view Intent Learning and Alignment with Large Language Models for Session-based Recommendation","date":"2024-02-21","arxiv_id":"2402.13840","repositories_listed":1,"syntology":null}],"syntology_records":12,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}