{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T15:12:41Z","timestamp":1767021161927,"version":"3.48.0"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T00:00:00Z","timestamp":1766966400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T00:00:00Z","timestamp":1766966400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Discov Artif Intell"],"DOI":"10.1007\/s44163-025-00650-w","type":"journal-article","created":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T15:07:54Z","timestamp":1767020874000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic intent-aware and cross-session integration for session-based recommendation"],"prefix":"10.1007","volume":"5","author":[{"given":"Keqin","family":"Jiang","sequence":"first","affiliation":[]},{"given":"Anyu","family":"Pan","sequence":"additional","affiliation":[]},{"given":"Yuchen","family":"Jiang","sequence":"additional","affiliation":[]},{"given":"Shulin","family":"Cheng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,12,29]]},"reference":[{"issue":"6","key":"650_CR1","doi-asserted-by":"publisher","first-page":"7685","DOI":"10.1109\/TCSS.2024.3446289","volume":"11","author":"L Guo","year":"2024","unstructured":"Guo L, Liu T, Zhou S, Tang H, Zheng X, Luo Y. Knowledge graph-based personalized multitask enhanced recommendation. IEEE Trans Comput Soc Syst. 2024;11(6):7685\u201397. https:\/\/doi.org\/10.1109\/TCSS.2024.3446289.","journal-title":"IEEE Trans Comput Soc Syst"},{"key":"650_CR2","doi-asserted-by":"publisher","unstructured":"Li A, Yang B, Huo H, Hussain F, Xu G. Hypercomplex knowledge graph-aware recommendation. In: Proceedings of the 48th international ACM SIGIR conference on research and development in information retrieval. SIGIR \u201925. Padua: Association for Computing Machinery, p. 2017\u20132026 (2025). https:\/\/doi.org\/10.1145\/3726302.3730001","DOI":"10.1145\/3726302.3730001"},{"key":"650_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2025.127430","volume":"282","author":"Y Cui","year":"2025","unstructured":"Cui Y, Wang K, Yu H, Guo X, Cao H. KLLMs4Rec: knowledge graph-enhanced LLMs sentiment extraction for personalized recommendations. Expert Syst Appl. 2025;282:127430. https:\/\/doi.org\/10.1016\/j.eswa.2025.127430.","journal-title":"Expert Syst Appl"},{"issue":"1","key":"650_CR4","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1325\/1\/012087","volume":"1325","author":"W Huang","year":"2019","unstructured":"Huang W, Liu B, Tang H. Privacy protection for recommendation system: a survey. J Phys Conf Ser. 2019;1325(1):012087. https:\/\/doi.org\/10.1088\/1742-6596\/1325\/1\/012087.","journal-title":"J Phys Conf Ser"},{"key":"650_CR5","doi-asserted-by":"publisher","unstructured":"Rendle S, Freudenthaler C, Schmidt-Thieme L. Factorizing personalized Markov chains for next-basket recommendation. In: Proceedings of the 19th international conference on World Wide Web. WWW \u201910. Raleigh: Association for Computing Machinery, 2010; p. 811\u2013820. https:\/\/doi.org\/10.1145\/1772690.1772773","DOI":"10.1145\/1772690.1772773"},{"key":"650_CR6","doi-asserted-by":"publisher","DOI":"10.1007\/s44443-025-00038-x","author":"W Jin","year":"2025","unstructured":"Jin W, Su D, Tao T, Wang X, Wang N, Zhao B. Courtroom-FND: a multi-role fake news detection method based on argument switching-based courtroom debate. J King Saud Univ Comput Inf Sci. 2025. https:\/\/doi.org\/10.1007\/s44443-025-00038-x.","journal-title":"J King Saud Univ Comput Inf Sci"},{"key":"650_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2025.110122","volume":"144","author":"W Jin","year":"2025","unstructured":"Jin W, Wang N, Tao T, Jiang M, Xing Y, Zhao B, et al. A prompting multi-task learning-based veracity dissemination consistency reasoning augmentation for few-shot fake news detection. Eng Appl Artif Intell. 2025;144:110122. https:\/\/doi.org\/10.1016\/j.engappai.2025.110122.","journal-title":"Eng Appl Artif Intell"},{"issue":"1","key":"650_CR8","doi-asserted-by":"publisher","first-page":"5920142","DOI":"10.1155\/int\/5920142","volume":"2025","author":"W Jin","year":"2025","unstructured":"Jin W, Gao Y, Tao T, Wang X, Wang N, Wu B, et al. Veracity-oriented context-aware large language models-based prompting optimization for fake news detection. Int J Intell Syst. 2025;2025(1):5920142. https:\/\/doi.org\/10.1155\/int\/5920142.","journal-title":"Int J Intell Syst"},{"key":"650_CR9","unstructured":"Hidasi B, Karatzoglou A, Baltrunas L, Tikk D. Session-based Recommendations with Recurrent Neural Networks. 2015:1511\u201306939. Preprint at arXiv:1511.06939 [cs.LG]"},{"key":"650_CR10","doi-asserted-by":"publisher","unstructured":"Chen J, He J, Li H, Wang S, Cao Y, Wei K, Yang Z, Ji Y. Hierarchical intent-guided optimization with pluggable LLM-driven semantics for session-based recommendation. In: Proceedings of the 48th international ACM SIGIR conference on research and development in information retrieval. SIGIR \u201925. Padua: Association for Computing Machinery, 2025; p. 1655\u20131665. https:\/\/doi.org\/10.1145\/3726302.3729994","DOI":"10.1145\/3726302.3729994"},{"key":"650_CR11","doi-asserted-by":"publisher","unstructured":"Sarwar B, Karypis G, Konstan J, Riedl J. Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th international conference on World Wide Web. WWW \u201901. Hong Kong: Association for Computing Machinery, 2001; p. 285\u2013295. https:\/\/doi.org\/10.1145\/371920.372071","DOI":"10.1145\/371920.372071"},{"key":"650_CR12","doi-asserted-by":"publisher","unstructured":"Li J, Ren P, Chen Z, Ren Z, Lian T, Ma J. Neural attentive session-based recommendation. In: Proceedings of the 2017 ACM on conference on information and knowledge management. CIKM \u201917. Singapore: Association for Computing Machinery, 2017; p. 1419\u20131428. https:\/\/doi.org\/10.1145\/3132847.3132926","DOI":"10.1145\/3132847.3132926"},{"key":"650_CR13","doi-asserted-by":"publisher","unstructured":"Xu C, Zhao P, Liu Y, Sheng VS, Xu J, Zhuang F, Fang J, Zhou X. Graph contextualized self-attention network for session-based recommendation. In: Proceedings of the 28th international joint conference on artificial intelligence. IJCAI\u201919. Macao: AAAI Press, 2019; p. 3940\u20133946. https:\/\/doi.org\/10.5555\/3367471.3367589","DOI":"10.5555\/3367471.3367589"},{"key":"650_CR14","doi-asserted-by":"publisher","unstructured":"Wu S, Tang Y, Zhu Y, Wang L, Xie X, Tan T. Session-based recommendation with graph neural networks. In: Proceedings of the thirty-third AAAI conference on artificial intelligence and thirty-first innovative applications of artificial intelligence conference and ninth AAAI symposium on educational advances in artificial intelligence. AAAI\u201919. Honolulu: AAAI Press; 2019. https:\/\/doi.org\/10.1609\/aaai.v33i01.3301346","DOI":"10.1609\/aaai.v33i01.3301346"},{"key":"650_CR15","doi-asserted-by":"publisher","unstructured":"Chen T, Wong RCW. Handling information loss of graph neural networks for session-based recommendation. In: Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining. KDD \u201920. Association for Computing Machinery, Virtual Event, 2020; p. 1172\u20131180. https:\/\/doi.org\/10.1145\/3394486.3403170","DOI":"10.1145\/3394486.3403170"},{"key":"650_CR16","doi-asserted-by":"publisher","unstructured":"Pan Z, Cai F, Chen W, Chen H, Rijke M. Star graph neural networks for session-based recommendation. In: Proceedings of the 29th ACM international conference on information & knowledge management. CIKM \u201920. Association for Computing Machinery, Virtual Event, 2020; p. 1195\u20131204. https:\/\/doi.org\/10.1145\/3340531.3412014","DOI":"10.1145\/3340531.3412014"},{"key":"650_CR17","doi-asserted-by":"publisher","unstructured":"Tang J, Wang K. Personalized top-n sequential recommendation via convolutional sequence embedding. In: Proceedings of the eleventh ACM international conference on web search and data mining. WSDM \u201918. Marina Del Rey: Association for Computing Machinery, 2018; p. 565\u2013573. https:\/\/doi.org\/10.1145\/3159652.3159656","DOI":"10.1145\/3159652.3159656"},{"key":"650_CR18","doi-asserted-by":"publisher","unstructured":"You J, Wang Y, Pal A, Eksombatchai P, Rosenburg C, Leskovec J. Hierarchical temporal convolutional networks for dynamic recommender systems. In: The World Wide Web Conference. WWW \u201919. San Francisco: Association for Computing Machinery, 2019; p. 2236\u20132246. https:\/\/doi.org\/10.1145\/3308558.3313747","DOI":"10.1145\/3308558.3313747"},{"key":"650_CR19","doi-asserted-by":"publisher","unstructured":"Tegene AT, Liu Q, Gan Y, Jimale E, Ayenew M, Leka H. A hybrid CNN-GRU model for session-based recommender systems. In: 2023 9th international conference on computer and communications (ICCC), 2023; p. 1988\u20131992. https:\/\/doi.org\/10.1109\/ICCC59590.2023.10507595","DOI":"10.1109\/ICCC59590.2023.10507595"},{"key":"650_CR20","doi-asserted-by":"publisher","unstructured":"Liu Q, Zeng Y, Mokhosi R, Zhang H. Stamp: Short-term attention\/memory priority model for session-based recommendation. In: Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining. KDD \u201918. London: Association for Computing Machinery; 2018, p. 1831\u20131839. https:\/\/doi.org\/10.1145\/3219819.3219950","DOI":"10.1145\/3219819.3219950"},{"key":"650_CR21","unstructured":"Devlin J, Chang MW, Lee K, Toutanova K. BERT: pre-training of deep bidirectional transformers for language understanding. In: Burstein J, Doran C, Solorio T, editors. Proceedings of the 2019 conference of the North American chapter of the association for computational Linguistics: human language technologies, Volume 1 (Long and Short Papers). Minneapolis: Association for Computational Linguistics, 2019; p. 4171\u20134186. https:\/\/aclanthology.org\/N19-1423\/"},{"key":"650_CR22","doi-asserted-by":"publisher","unstructured":"Sun F, Liu J, Wu J, Pei C, Lin X, Ou W, Jiang P. BERT4Rec: sequential recommendation with bidirectional encoder representations from transformer. In: Proceedings of the 28th ACM international conference on information and knowledge management. CIKM \u201919. Beijing: Association for Computing Machinery, 2019; p. 1441\u20131450. https:\/\/doi.org\/10.1145\/3357384.3357895","DOI":"10.1145\/3357384.3357895"},{"key":"650_CR23","doi-asserted-by":"crossref","unstructured":"Luo A, Zhao P, Liu Y, Zhuang F, Wang D, Xu J, Fang J, Sheng VS. Collaborative self-attention network for session-based recommendation. In: Proceedings of the twenty-ninth international joint conference on artificial intelligence. IJCAI\u201920, Yokohama, 2021. https:\/\/dl.acm.org\/doi\/abs\/10.5555\/3491440.3491799","DOI":"10.24963\/ijcai.2020\/359"},{"key":"650_CR24","doi-asserted-by":"publisher","unstructured":"Zhou K, Wang H, Zhao WX, Zhu Y, Wang S, Zhang F, Wang Z, Wen JR. S3-rec: self-supervised learning for sequential recommendation with mutual information maximization. In: Proceedings of the 29th ACM international conference on information & knowledge management. CIKM \u201920. Association for Computing Machinery, Virtual Event, 2020; p. 1893\u20131902. https:\/\/doi.org\/10.1145\/3340531.3411954","DOI":"10.1145\/3340531.3411954"},{"key":"650_CR25","doi-asserted-by":"crossref","unstructured":"Yuan J, Song Z, Sun M, Wang X, Zhao WX. Dual sparse attention network for session-based recommendation. In: Proceedings of the AAAI conference on artificial intelligence, vol. 35, 2021; p. 4635\u20134643. https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/16593","DOI":"10.1609\/aaai.v35i5.16593"},{"key":"650_CR26","doi-asserted-by":"publisher","unstructured":"Wang M, Ren P, Mei L, Chen Z, Ma J, Rijke M. A collaborative session-based recommendation approach with parallel memory modules. In: Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval. SIGIR\u201919. Paris: Association for Computing Machinery, 2019; p. 345\u2013354. https:\/\/doi.org\/10.1145\/3331184.3331210","DOI":"10.1145\/3331184.3331210"},{"key":"650_CR27","doi-asserted-by":"publisher","unstructured":"Wang Z, Wei W, Cong G, Li XL, Mao XL, Qiu M. Global context enhanced graph neural networks for session-based recommendation. In: Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval. SIGIR \u201920. Association for Computing Machinery, Virtual Event, 2020; p. 169\u2013178. https:\/\/doi.org\/10.1145\/3397271.3401142","DOI":"10.1145\/3397271.3401142"},{"key":"650_CR28","doi-asserted-by":"publisher","unstructured":"Huang C, Chen J, Xia L, Xu Y, Dai P, Chen Y, et al. Graph-enhanced multi-task learning of multi-level transition dynamics for session-based recommendation. In: Proceedings of the AAAI conference on artificial intelligence. vol. 35, 2021; p. 4123\u201330. https:\/\/doi.org\/10.1609\/aaai.v35i5.16534.","DOI":"10.1609\/aaai.v35i5.16534"},{"key":"650_CR29","doi-asserted-by":"publisher","unstructured":"Xia X, Yin H, Yu J, Wang Q, Cui L, Zhang X. Self-supervised hypergraph convolutional networks for session-based recommendation. In: Proceedings of the AAAI conference on artificial intelligence. vol. 35, 2021; p. 4503\u201311. https:\/\/doi.org\/10.1609\/aaai.v35i5.16578.","DOI":"10.1609\/aaai.v35i5.16578"},{"key":"650_CR30","doi-asserted-by":"publisher","unstructured":"Xia X, Yin H, Yu J, Shao Y, Cui L. Self-supervised graph co-training for session-based recommendation. In: Proceedings of the 30th ACM international conference on information & knowledge management. CIKM \u201921. Queensland: Association for Computing Machinery, Virtual Event, 2021; p. 2180\u20132190. https:\/\/doi.org\/10.1145\/3459637.3482388","DOI":"10.1145\/3459637.3482388"},{"key":"650_CR31","doi-asserted-by":"publisher","unstructured":"Pan Z, Cai F, Ling Y, Rijke M. An intent-guided collaborative machine for session-based recommendation. In: Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval. SIGIR \u201920. Association for Computing Machinery, Virtual Event, 2020; p. 1833\u20131836. https:\/\/doi.org\/10.1145\/3397271.3401273","DOI":"10.1145\/3397271.3401273"},{"key":"650_CR32","doi-asserted-by":"publisher","unstructured":"Li Y, Gao C, Luo H, Jin D, Li Y. Enhancing hypergraph neural networks with intent disentanglement for session-based recommendation. In: Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval. SIGIR \u201922. Madrid: Association for Computing Machinery, 2022; p. 1997\u20132002. https:\/\/doi.org\/10.1145\/3477495.3531794","DOI":"10.1145\/3477495.3531794"},{"issue":"3","key":"650_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2022.102936","volume":"59","author":"X Zhang","year":"2022","unstructured":"Zhang X, Lin H, Xu B, Li C, Lin Y, Liu H, et al. Dynamic intent-aware iterative denoising network for session-based recommendation. Inf Process Manag. 2022;59(3):102936. https:\/\/doi.org\/10.1016\/j.ipm.2022.102936.","journal-title":"Inf Process Manag"},{"issue":"1","key":"650_CR34","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1007\/s11280-022-01036-z","volume":"26","author":"B Yu","year":"2023","unstructured":"Yu B, Li X, Fang J, Tai C, Cheng W, Xu J. Memory-augmented meta-learning framework for session-based target behavior recommendation. World Wide Web. 2023;26(1):233\u201351. https:\/\/doi.org\/10.1007\/s11280-022-01036-z.","journal-title":"World Wide Web"},{"key":"650_CR35","doi-asserted-by":"publisher","DOI":"10.1145\/3663760","author":"X Zhuo","year":"2024","unstructured":"Zhuo X, Qian S, Hu J, Dai F, Lin K, Wu G. Multi-hop multi-view memory transformer for session-based recommendation. ACM Trans Inf Syst. 2024. https:\/\/doi.org\/10.1145\/3663760.","journal-title":"ACM Trans Inf Syst"},{"key":"650_CR36","doi-asserted-by":"publisher","unstructured":"Liu M, Gao H, Ji S. Towards deeper graph neural networks. In: Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining. KDD \u201920. Association for Computing Machinery, Virtual Event, 2020; p. 338\u2013348. https:\/\/doi.org\/10.1145\/3394486.3403076","DOI":"10.1145\/3394486.3403076"},{"key":"650_CR37","unstructured":"Luo D, Wang X. ModernTCN: a modern pure convolution structure for general time series analysis. In: The twelfth international conference on learning representations. 2024. https:\/\/openreview.net\/forum?id=vpJMJerXHU"},{"key":"650_CR38","doi-asserted-by":"publisher","unstructured":"Zangerle E, Pichl M, Gassler W, Specht G. #nowplaying music dataset: extracting listening behavior from twitter. In: Proceedings of the first international workshop on internet-scale multimedia management. WISMM \u201914. Orlando: Association for Computing Machinery, 2014; p. 21\u201326. https:\/\/doi.org\/10.1145\/2661714.2661719","DOI":"10.1145\/2661714.2661719"},{"key":"650_CR39","doi-asserted-by":"publisher","unstructured":"Garg D, Gupta P, Malhotra P, Vig L, Shroff G. Sequence and time aware neighborhood for session-based recommendations: Stan. In: Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval. SIGIR\u201919. Paris: Association for Computing Machinery, 2019; p. 1069\u20131072. https:\/\/doi.org\/10.1145\/3331184.3331322","DOI":"10.1145\/3331184.3331322"},{"key":"650_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109204","volume":"251","author":"G Tang","year":"2022","unstructured":"Tang G, Zhu X, Guo J, Dietze S. Time enhanced graph neural networks for session-based recommendation. Knowl-Based Syst. 2022;251:109204. https:\/\/doi.org\/10.1016\/j.knosys.2022.109204.","journal-title":"Knowl-Based Syst"},{"key":"650_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122773","volume":"242","author":"Z Zhang","year":"2024","unstructured":"Zhang Z, Yang B, Xu H, Hu W. Multi-level category-aware graph neural network for session-based recommendation. Expert Syst Appl. 2024;242:122773. https:\/\/doi.org\/10.1016\/j.eswa.2023.122773.","journal-title":"Expert Syst Appl"},{"key":"650_CR42","unstructured":"Zhang S, Li X, Wu J, Yang F, Li X, Gao M. Integrating LLM-derived multi-semantic intent into graph model for session-based recommendation. 2025. arXiv:2507.20147"}],"container-title":["Discover Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44163-025-00650-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44163-025-00650-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44163-025-00650-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T15:07:55Z","timestamp":1767020875000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44163-025-00650-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,29]]},"references-count":42,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["650"],"URL":"https:\/\/doi.org\/10.1007\/s44163-025-00650-w","relation":{},"ISSN":["2731-0809"],"issn-type":[{"value":"2731-0809","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,29]]},"assertion":[{"value":"12 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"399"}}