{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/multi-behavioral-sequential-recommendation","title":"Multi-Behavioral Sequential Recommendation","arxiv_id":null,"date":"2024-10-08","proceeding":"RecSys 2024 10","authors":["Shereen Elsayed","Ahmed Rashed","Lars Schmidt-Thieme"],"abstract":"Sequential recommendation models are crucial for next-item prediction tasks in various online platforms, yet many focus on a single behavior, neglecting valuable implicit interactions. While multi-behavioral models address this using graph-based approaches, they often fail to capture sequential patterns simultaneously. Our proposed Multi-Behavioral Sequential Recommendation framework (MBSRec) captures the multi-behavior dependencies between the heterogeneous historical interactions via multi-head self-attention. Furthermore, we utilize a weighted binary cross-entropy loss for precise behavior control. Experimental results on four datasets demonstrate MBSRec’s significant outperformance of state-of-the-art approaches. The implementation code is available here https://github.com/Shereen-Elsayed/MBSRec.","url_abs":"https://dl.acm.org/doi/abs/10.1145/3640457.3688166","url_pdf":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688166","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"multi-behavioral-sequential-recommendation","repo_url":"https://github.com/Shereen-Elsayed/MBSRec","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"multibehavior-recommendation","task_name":"Multibehavior Recommendation"},{"task_slug":"recommendation-systems","task_name":"Recommendation Systems"},{"task_slug":"sequential-recommendation","task_name":"Sequential Recommendation"}],"methods":[{"method_slug":"focus","method_name":"Focus"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/multibehavior-recommendation-on-movielens","task":"Multibehavior Recommendation","dataset":"MovieLens","model":"MBSRec","rank_in_archive_order":2,"of":4,"metrics":{"HR@10":"0.930"},"uses_additional_data":false},{"leaderboard":"/sota/multibehavior-recommendation-on-multi","task":"Multibehavior Recommendation","dataset":"Multi-behavior Taobao","model":"MBSRec","rank_in_archive_order":2,"of":4,"metrics":{"HR@10":"0.841"},"uses_additional_data":false},{"leaderboard":"/sota/multibehavior-recommendation-on-yelp","task":"Multibehavior Recommendation","dataset":"Yelp","model":"MBSRec","rank_in_archive_order":2,"of":4,"metrics":{"HR@10":"0.898"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}