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Knowl. Discov. Data"],"published-print":{"date-parts":[[2026,6,30]]},"abstract":"<jats:p>Deep reinforcement learning (DRL), has shown promise in solving intractable challenges in interactive recommendation systems (IRS). In DRL-based interactive recommendation, state modeling is vital for well-capturing users\u2019 continuous interaction behaviors with recommendation systems. To effectively capture the behavior of users, existing works for state modeling have evolved from sequential-based modeling to session-based modeling. However, existing session-based state modeling works in IRS are still not fully explored with premature session models and insufficient fusion for different session features. As a result, they cannot capture complicated session patterns during interaction, leading to significant information loss. In this article, we propose a Knowledge-enhanced Multi-Level Session Graph (KMSG) model for interactive recommendation to address the above challenge. KMSG models the user\u2019s interactive data into multi-level session graphs and effectively encodes the states via graph neural networks. Specifically, a novel 3-level item transition graph is designed to capture the common session patterns and intra-session item transitions. We further utilize the information from the knowledge graph to enhance the item relations in KMSG. We then design an attention-based graph neural network to propagate the information in KMSG. Extensive experiments on four real-world benchmark datasets demonstrate the superiority of KMSG over state-of-the-art baselines and the rationality of our design in KMSG.<\/jats:p>","DOI":"10.1145\/3811912","type":"journal-article","created":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T12:28:14Z","timestamp":1777292894000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Knowledge-Enhanced Multi-Level Session Graph Model for Interactive Recommendation through Deep Reinforcement Learning"],"prefix":"10.1145","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4334-1182","authenticated-orcid":false,"given":"Longxiang","family":"Shi","sequence":"first","affiliation":[{"name":"College of Computer and Computing Science, Hangzhou City University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-6015-8576","authenticated-orcid":false,"given":"Rui","family":"Hu","sequence":"additional","affiliation":[{"name":"College of Computer and Computing Science, Hangzhou City University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9161-4352","authenticated-orcid":false,"given":"Zilin","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1133-9379","authenticated-orcid":false,"given":"Shoujin","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Technology Sydney, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1037-1361","authenticated-orcid":false,"given":"Qi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tongji University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7152-7841","authenticated-orcid":false,"given":"Kui","family":"Su","sequence":"additional","affiliation":[{"name":"College of Computer and Computing Science, Hangzhou City University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8309-5524","authenticated-orcid":false,"given":"Cheng","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Computer and Computing Science, Hangzhou City University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5846-3065","authenticated-orcid":false,"given":"Shijian","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,3]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3543846","article-title":"Reinforcement learning based recommender systems: A survey","volume":"55","author":"Afsar M. 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