{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T15:00:04Z","timestamp":1779375604211,"version":"3.53.1"},"reference-count":74,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2025,5,22]],"date-time":"2025-05-22T00:00:00Z","timestamp":1747872000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,5,22]],"date-time":"2025-05-22T00:00:00Z","timestamp":1747872000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1007\/s10115-025-02455-w","type":"journal-article","created":{"date-parts":[[2025,5,22]],"date-time":"2025-05-22T15:57:00Z","timestamp":1747929420000},"page":"7727-7755","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Diversity-enhanced conversational recommendation via multi-agent reinforcement learning"],"prefix":"10.1007","volume":"67","author":[{"given":"Zihan","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shi","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daling","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaisong","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gang","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Han","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ge","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,5,22]]},"reference":[{"key":"2455_CR1","doi-asserted-by":"crossref","unstructured":"Schafer JB, Frankowski D, Herlocker J, Sen S (2007) Collaborative filtering recommender systems. In: The adaptive web: methods and strategies of web personalization, pp 291\u2013324","DOI":"10.1007\/978-3-540-72079-9_9"},{"key":"2455_CR2","doi-asserted-by":"crossref","unstructured":"Kang W, McAuley JJ (2018) Self-attentive sequential recommendation. CoRR abs\/1808.09781","DOI":"10.1109\/ICDM.2018.00035"},{"key":"2455_CR3","doi-asserted-by":"crossref","unstructured":"Christakopoulou K, Radlinski F, Hofmann K (2016) Towards conversational recommender systems. In: Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining, pp 815\u2013824","DOI":"10.1145\/2939672.2939746"},{"key":"2455_CR4","doi-asserted-by":"publisher","unstructured":"Zhang Y, Chen X, Ai Q, Yang L, Croft WB (2018) Towards conversational search and recommendation: system ask, user respond. In: Cuzzocrea A, Allan J, Paton N, Srivastava D, Agrawal R, Broder A, Zaki M, Candan S, Labrinidis A, Schuster A, Wang H (eds) CIKM\u201918: proceedings of the 27th ACM international conference on information and knowledge management, pp 177\u2013186 (2018). https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3269206.3271776 . Assoc Comp Machinery; Assoc Comp Machinery Special Interest Grp Informat Retrieval; Assoc Comp Machinery SIGWEB; Univ Trieste. 27th ACM International Conference on Information and Knowledge Management (CIKM), Torino","DOI":"10.1145\/3269206.3271776"},{"key":"2455_CR5","doi-asserted-by":"publisher","unstructured":"Chen Z, Wang X, Xie X, Parsana M, Soni A, Ao X, Chen E (2020) Towards explainable conversational recommendation. In: Bessiere C (ed) Proceedings of the twenty-ninth international joint conference on artificial intelligence, IJCAI 2020, pp 2994\u20133000. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.24963\/IJCAI.2020\/414","DOI":"10.24963\/IJCAI.2020\/414"},{"key":"2455_CR6","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1016\/J.AIOPEN.2021.06.002","volume":"2","author":"C Gao","year":"2021","unstructured":"Gao C, Lei W, He X, Rijke M, Chua T (2021) Advances and challenges in conversational recommender systems: a survey. AI Open 2:100\u2013126. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/J.AIOPEN.2021.06.002","journal-title":"AI Open"},{"key":"2455_CR7","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1145\/3453154","volume":"54","author":"D Jannach","year":"2021","unstructured":"Jannach D, Manzoor A, Cai W, Chen L (2021) A survey on conversational recommender systems. ACM Comput Surv 54:5. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3453154","journal-title":"ACM Comput Surv"},{"key":"2455_CR8","doi-asserted-by":"publisher","unstructured":"Zhang Y, Wu L, Shen Q, Pang Y, Wei Z, Xu F, Long B, Pei J (2022) Multiple choice questions based multi-interest policy learning for conversational recommendation. In: Laforest F, Troncy R, Simperl E, Agarwal D, Gionis A, Herman I, M\u00e9dini L (eds) WWW \u201922: the ACM web conference 2022, virtual event, Lyon, France, April 25\u201329, 2022, pp 2153\u20132162. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3485447.3512088","DOI":"10.1145\/3485447.3512088"},{"key":"2455_CR9","doi-asserted-by":"publisher","unstructured":"Deng Y, Li Y, Sun F, Ding B, Lam W (2021) Unified conversational recommendation policy learning via graph-based reinforcement learning. In: Diaz F, Shah C, Suel T, Castells P, Jones R, Sakai T (eds) SIGIR \u201921: the 44th international ACM SIGIR conference on research and development in information retrieval, virtual event, Canada, July 11\u201315, 2021, pp 1431\u20131441. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3404835.3462913","DOI":"10.1145\/3404835.3462913"},{"key":"2455_CR10","doi-asserted-by":"crossref","unstructured":"Li SE (2023) Deep reinforcement learning. In: Reinforcement learning for sequential decision and optimal control, pp 365\u2013402","DOI":"10.1007\/978-981-19-7784-8_10"},{"key":"2455_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/J.INFFUS.2022.03.003","volume":"85","author":"P Ladosz","year":"2022","unstructured":"Ladosz P, Weng L, Kim M, Oh H (2022) Exploration in deep reinforcement learning: a survey. Inf Fusion 85:1\u201322. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/J.INFFUS.2022.03.003","journal-title":"Inf Fusion"},{"issue":"11","key":"2455_CR12","doi-asserted-by":"publisher","first-page":"11541","DOI":"10.1109\/TKDE.2022.3225109","volume":"35","author":"Y Deng","year":"2023","unstructured":"Deng Y, Li Y, Ding B, Lam W (2023) Leveraging long short-term user preference in conversational recommendation via multi-agent reinforcement learning. IEEE Trans Knowl DATA Eng 35(11):11541\u201311555. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1109\/TKDE.2022.3225109","journal-title":"IEEE Trans Knowl DATA Eng"},{"key":"2455_CR13","doi-asserted-by":"publisher","unstructured":"Lei W, Zhang G, He X, Miao Y, Wang X, Chen L, Chua T-S (2020) Interactive path reasoning on graph for conversational recommendation. In: KDD \u201820: proceedings of the 26th ACM sigkdd international conference on knowledge discovery and data mining. Assoc Comp Machinery; ACM SIGMOD; ACM SIGKDD, pp 2073\u20132083. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3394486.3403258","DOI":"10.1145\/3394486.3403258"},{"key":"2455_CR14","doi-asserted-by":"crossref","unstructured":"Lei W, He X, Miao Y, Wu Q, Hong R, Kan M-Y, Chua T-S (2020) Estimation-action-reflection: Towards deep interaction between conversational and recommender systems. In: Proceedings of the 13th international conference on web search and data mining, pp 304\u2013312","DOI":"10.1145\/3336191.3371769"},{"key":"2455_CR15","doi-asserted-by":"publisher","unstructured":"Wang W, Feng F, Nie L, Chua T (2022) User-controllable recommendation against filter bubbles. In: Amig\u00f3 E, Castells P, Gonzalo J, Carterette B, Culpepper JS, Kazai G (eds) SIGIR \u201922: the 45th international ACM SIGIR conference on research and development in information retrieval, Madrid, Spain, July 11\u201315, pp 1251\u20131261. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3477495.3532075","DOI":"10.1145\/3477495.3532075"},{"key":"2455_CR16","doi-asserted-by":"publisher","unstructured":"Wu Q, Liu Y, Miao C, Zhao B, Zhao Y, Guan L (2019) PD-GAN: adversarial learning for personalized diversity-promoting recommendation. In: Kraus S (ed) Proceedings of the twenty-eighth international joint conference on artificial intelligence, IJCAI 2019, Macao, China, August 10\u201316, pp 3870\u20133876. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.24963\/IJCAI.2019\/537","DOI":"10.24963\/IJCAI.2019\/537"},{"key":"2455_CR17","doi-asserted-by":"publisher","unstructured":"Lu Y, Zhang S, Huang Y, Wang L, Yu X, Zhao Z, Wu F (2021) Future-aware diverse trends framework for recommendation. In: Leskovec J, Grobelnik M, Najork M, Tang J, Zia L (eds) WWW \u201921: the web conference 2021, virtual event\/Ljubljana, Slovenia, April 19\u201323, pp 2992\u20133001. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3442381.3449791","DOI":"10.1145\/3442381.3449791"},{"key":"2455_CR18","doi-asserted-by":"publisher","unstructured":"Chen W, Ren P, Cai F, Sun F, Rijke M (2020) Improving end-to-end sequential recommendations with intent-aware diversification. In: d\u2019Aquin M, Dietze S, Hauff C, Curry E, Cudr\u00e9-Mauroux P (eds) CIKM \u201920: the 29th ACM international conference on information and knowledge management, virtual event, Ireland, October 19\u201323, 2020, pp 175\u2013184. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3340531.3411897","DOI":"10.1145\/3340531.3411897"},{"key":"2455_CR19","doi-asserted-by":"publisher","unstructured":"Ding Q, Liu Y, Miao C, Cheng F, Tang H (2021) A hybrid bandit framework for diversified recommendation. In: Thirty-Fifth AAAI conference on artificial intelligence, AAAI 2021, thirty-third conference on innovative applications of artificial intelligence, IAAI 2021, the eleventh symposium on educational advances in artificial intelligence, EAAI 2021, Virtual Event, February 2\u20139, 2021, pp 4036\u20134044. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1609\/AAAI.V35I5.16524","DOI":"10.1609\/AAAI.V35I5.16524"},{"key":"2455_CR20","doi-asserted-by":"publisher","unstructured":"Zhao Z, Zhou K, Wang X, Zhao WX, Pan F, Cao Z, Wen J (2023) Alleviating the long-tail problem in conversational recommender systems. In: Zhang J, Chen L, Berkovsky S, Zhang M, Noia TD, Basilico J, Pizzato L, Song Y (eds) Proceedings of the 17th ACM conference on recommender systems, RecSys 2023, Singapore, Singapore, September 18\u201322, 2023, pp 374\u2013385. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3604915.3608812","DOI":"10.1145\/3604915.3608812"},{"key":"2455_CR21","doi-asserted-by":"crossref","unstructured":"Peng K, Raghavan M, Pierson E, Kleinberg J, Garg N (2024) Reconciling the accuracy-diversity trade-off in recommendations. In: Proceedings of the ACM on web conference 2024, pp 1318\u20131329","DOI":"10.1145\/3589334.3645625"},{"key":"2455_CR22","unstructured":"Baker B, Kanitscheider I, Markov TM, Wu Y, Powell G, McGrew B, Mordatch I (2020) Emergent tool use from multi-agent autocurricula. In: 8th International conference on learning representations, ICLR 2020, Addis Ababa, Ethiopia, April 26\u201330, 2020"},{"key":"2455_CR23","unstructured":"Leibo JZ, Zambaldi V, Lanctot M, Marecki J, Graepel T (2017) Multi-agent reinforcement learning in sequential social dilemmas. In: AAMAS\u201917: proceedings of the 16th international conference on autonomous agents and multiagent systems, pp 464\u2013473. IFAAMAS; FAPESP; Coordenacao Aperfeicoamento Pessoal Nivel Super; IBM Res; Microsoft; Univ OTAGO; Univ Waterloo, Fac Math, David R Cheriton Sch Comp Sci; DeepMind; Univ Sao Paulo; Scopus; Assoc Comp Machinery; Univ Sao Paulo, Escola Politecnica; Univ Waterloo. 16th international conference on autonomous agents and multiagent systems (AAMAS), Sao Paulo, BRAZIL, MAY 08-12, 2017"},{"issue":"9","key":"2455_CR24","doi-asserted-by":"publisher","first-page":"896","DOI":"10.14778\/2311906.2311916","volume":"5","author":"H Yin","year":"2012","unstructured":"Yin H, Cui B, Li J, Yao J, Chen C (2012) Challenging the long tail recommendation. Proc VLDB Endow 5(9):896\u2013907. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.14778\/2311906.2311916","journal-title":"Proc VLDB Endow"},{"key":"2455_CR25","doi-asserted-by":"crossref","unstructured":"Liu S, Zheng Y (2020) Long-tail session-based recommendation. CoRR abs\/2007.12329","DOI":"10.1145\/3383313.3412222"},{"key":"2455_CR26","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1016\/J.KNOSYS.2017.02.009","volume":"123","author":"M Kunaver","year":"2017","unstructured":"Kunaver M, Pozrl T (2017) Diversity in recommender systems\u2014a survey. Knowl Based Syst 123:154\u2013162. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/J.KNOSYS.2017.02.009","journal-title":"Knowl Based Syst"},{"key":"#cr-split#-2455_CR27.1","unstructured":"Qin L, Zhu X (2013) Promoting diversity in recommendation by entropy regularizer. In: Rossi F"},{"key":"#cr-split#-2455_CR27.2","unstructured":"(ed) IJCAI 2013, proceedings of the 23rd international joint conference on artificial intelligence, Beijing, China, August 3-9, pp 2698-2704"},{"issue":"4","key":"2455_CR28","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1145\/3446427","volume":"39","author":"S Li","year":"2021","unstructured":"Li S, Lei W, Wu Q, He X, Jiang P, Chua T (2021) Seamlessly unifying attributes and items: conversational recommendation for cold-start users. ACM Trans Inf Syst 39(4):40\u201314029. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3446427","journal-title":"ACM Trans Inf Syst"},{"key":"2455_CR29","doi-asserted-by":"publisher","unstructured":"Christakopoulou K, Beutel A, Li R, Jain S, Chi EH (2018) Q &r: a two-stage approach toward interactive recommendation. In: Guo Y, Farooq F (eds) Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery and data mining, KDD 2018, London, UK, August 19\u201323, pp 139\u2013148. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3219819.3219894","DOI":"10.1145\/3219819.3219894"},{"key":"2455_CR30","doi-asserted-by":"publisher","unstructured":"Zhou K, Zhao WX, Bian S, Zhou Y, Wen J, Yu J (2020) Improving conversational recommender systems via knowledge graph based semantic fusion. In: Gupta R, Liu Y, Tang J, Prakash BA (eds) KDD \u201920: the 26th ACM SIGKDD conference on knowledge discovery and data mining, virtual event, CA, USA, August 23\u201327, 2020, pp 1006\u20131014. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3394486.3403143","DOI":"10.1145\/3394486.3403143"},{"key":"2455_CR31","doi-asserted-by":"publisher","unstructured":"Liu Z, Wang H, Niu Z, Wu H, Che W, Liu T (2020) Towards conversational recommendation over multi-type dialogs. In: Jurafsky D, Chai J, Schluter N, Tetreault JR (eds) Proceedings of the 58th annual meeting of the association for computational linguistics, ACL 2020, Online, July 5\u201310, 2020, pp. 1036\u20131049. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.18653\/V1\/2020.ACL-MAIN.98","DOI":"10.18653\/V1\/2020.ACL-MAIN.98"},{"key":"2455_CR32","unstructured":"Li R, Kahou SE, Schulz H, Michalski V, Charlin L, Pal C (2018) Towards deep conversational recommendations. In: Bengio S, Wallach HM, Larochelle H, Grauman K, Cesa-Bianchi N, Garnett R (eds) Advances in neural information processing systems 31: annual conference on neural information processing systems 2018, NeurIPS 2018, December 3\u20138, 2018, Montr\u00e9al, Canada, pp 9748\u20139758"},{"key":"2455_CR33","doi-asserted-by":"publisher","unstructured":"Zhou K, Zhou Y, Zhao WX, Wang X, Wen J (2020) Towards topic-guided conversational recommender system. In: Scott D, Bel N, Zong C (eds) Proceedings of the 28th international conference on computational linguistics, COLING 2020, Barcelona, Spain (Online), December 8\u201313, 2020, pp 4128\u20134139. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.18653\/V1\/2020.COLING-MAIN.365","DOI":"10.18653\/V1\/2020.COLING-MAIN.365"},{"key":"2455_CR34","unstructured":"Fang J, Gao S, Ren P, Chen X, Verberne S, Ren Z (2024) A multi-agent conversational recommender system. arXiv:2402.01135"},{"issue":"6","key":"2455_CR35","doi-asserted-by":"publisher","first-page":"4109","DOI":"10.1007\/S11280-023-01219-2","volume":"26","author":"S Fan","year":"2023","unstructured":"Fan S, Wang Y, Pang X, Chen L, Han P, Shang S (2023) Uamc: user-augmented conversation recommendation via multi-modal graph learning and context mining. World Wide Web (WWW) 26(6):4109\u20134129. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/S11280-023-01219-2","journal-title":"World Wide Web (WWW)"},{"key":"2455_CR36","doi-asserted-by":"crossref","unstructured":"Sun Y, Zhang Y (2018) Conversational recommender system. In: The 41st international Acm Sigir conference on research and development in information retrieval, pp 235\u2013244","DOI":"10.1145\/3209978.3210002"},{"key":"2455_CR37","doi-asserted-by":"publisher","unstructured":"Carbonell JG, Goldstein J (1998) The use of mmr, diversity-based reranking for reordering documents and producing summaries. In: Croft WB, Moffat A, Rijsbergen CJ, Wilkinson R, Zobel J (eds) SIGIR \u201998: proceedings of the 21st annual international ACM SIGIR conference on research and development in information retrieval, August 24\u201328 1998, Melbourne, Australia, pp 335\u2013336. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/290941.291025","DOI":"10.1145\/290941.291025"},{"key":"2455_CR38","doi-asserted-by":"publisher","unstructured":"Cheng P, Wang S, Ma J, Sun J, Xiong H (2017) Learning to recommend accurate and diverse items. In: Barrett R, Cummings R, Agichtein E, Gabrilovich E (eds) Proceedings of the 26th international conference on world wide web, WWW 2017, Perth, Australia, April 3\u20137, 2017, pp 183\u2013192. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3038912.3052585","DOI":"10.1145\/3038912.3052585"},{"key":"2455_CR39","doi-asserted-by":"publisher","unstructured":"Cen Y, Zhang J, Zou X, Zhou C, Yang H, Tang J (2020) Controllable multi-interest framework for recommendation. In: Gupta R, Liu Y, Tang J, Prakash BA (eds) KDD \u201920: the 26th ACM SIGKDD conference on knowledge discovery and data mining, virtual event, CA, USA, August 23\u201327, 2020, pp 2942\u20132951. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3394486.3403344","DOI":"10.1145\/3394486.3403344"},{"key":"2455_CR40","doi-asserted-by":"publisher","unstructured":"Bian S, Zhao WX, Wang J, Wen J (2022) A relevant and diverse retrieval-enhanced data augmentation framework for sequential recommendation. In: Hasan MA, Xiong L (eds) Proceedings of the 31st ACM international conference on information and knowledge management, Atlanta, GA, USA, October 17\u201321, 2022, pp 2923\u20132932. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3511808.3557071","DOI":"10.1145\/3511808.3557071"},{"issue":"1","key":"2455_CR41","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1007\/S11280-024-01242-X","volume":"27","author":"M He","year":"2024","unstructured":"He M, Zhang H, Zhang Z, Liu C (2024) Invariant representation learning to popularity distribution shift for recommendation. World Wide Web (WWW) 27(1):10. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/S11280-024-01242-X","journal-title":"World Wide Web (WWW)"},{"issue":"4","key":"2455_CR42","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1007\/S11280-024-01272-5","volume":"27","author":"H Zhou","year":"2024","unstructured":"Zhou H, Fang J, Chao P, Qu J, Zhang R (2024) Popgr: popularity reweighting for debiasing in group recommendation. World Wide Web (WWW) 27(4):34. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/S11280-024-01272-5","journal-title":"World Wide Web (WWW)"},{"key":"2455_CR43","doi-asserted-by":"crossref","unstructured":"El\u00a0Alaoui D, Riffi J, Sabri A, Aghoutane B, Yahyaouy A, Tairi H (2024) Social recommendation system based on heterogeneous graph attention networks. Int J Data Sci Anal 1\u201317","DOI":"10.1007\/s41060-024-00698-4"},{"key":"2455_CR44","doi-asserted-by":"crossref","unstructured":"El\u00a0Alaoui D, Riffi J, Aghoutane B, Sabri A, Yahyaouy A, Tairi H (2021) Collaborative filtering: comparative study between matrix factorization and neural network method. In: Networked systems: 8th international conference, NETYS 2020, Marrakech, Morocco, June 3\u20135, 2020, proceedings 8, pp 361\u2013367. Springer","DOI":"10.1007\/978-3-030-67087-0_24"},{"issue":"14","key":"2455_CR45","doi-asserted-by":"publisher","first-page":"11679","DOI":"10.1007\/s00521-022-07059-x","volume":"34","author":"D El Alaoui","year":"2022","unstructured":"El Alaoui D, Riffi J, Sabri A, Aghoutane B, Yahyaouy A, Tairi H (2022) Deep graphsage-based recommendation system: jumping knowledge connections with ordinal aggregation network. Neural Comput Appl 34(14):11679\u201311690","journal-title":"Neural Comput Appl"},{"issue":"12","key":"2455_CR46","doi-asserted-by":"publisher","first-page":"190","DOI":"10.3390\/bdcc8120190","volume":"8","author":"D El Alaoui","year":"2024","unstructured":"El Alaoui D, Riffi J, Sabri A, Aghoutane B, Yahyaouy A, Tairi H (2024) Comparative study of filtering methods for scientific research article recommendations. Big Data and Cognit Comput 8(12):190","journal-title":"Big Data and Cognit Comput"},{"key":"2455_CR47","doi-asserted-by":"crossref","unstructured":"El\u00a0Alaoui D, Riffi J, Sabri A, Aghoutane B, Yahyaouy A, Tairi H (2024) Contextual recommendations: dynamic graph attention networks with edge adaptation. IEEE Access","DOI":"10.1109\/ACCESS.2024.3477956"},{"key":"2455_CR48","doi-asserted-by":"crossref","unstructured":"El\u00a0Alaoui D, Riffi J, Sabri A, Aghoutane B, Yahyaouy A, Tairi H (2025) A novel session-based recommendation system using capsule graph neural network. Neural Netw 107176","DOI":"10.1016\/j.neunet.2025.107176"},{"key":"2455_CR49","doi-asserted-by":"publisher","unstructured":"Liu Y, Walder CJ, Xie L (2022) Determinantal point process likelihoods for sequential recommendation. In: Amig\u00f3 E, Castells P, Gonzalo J, Carterette B, Culpepper JS, Kazai G (eds) SIGIR \u201922: the 45th international ACM SIGIR conference on research and development in information retrieval, Madrid, Spain, July 11\u201315, 2022, pp 1653\u20131663. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3477495.3531965","DOI":"10.1145\/3477495.3531965"},{"key":"2455_CR50","doi-asserted-by":"publisher","unstructured":"Wang S, Hu L, Wang Y, Sheng QZ, Orgun MA, Cao L (2019) Modeling multi-purpose sessions for next-item recommendations via mixture-channel purpose routing networks. In: Kraus S (ed) Proceedings of the twenty-eighth international joint conference on artificial intelligence, IJCAI 2019, Macao, China, August 10\u201316, 2019, pp 3771\u20133777. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.24963\/IJCAI.2019\/523","DOI":"10.24963\/IJCAI.2019\/523"},{"key":"2455_CR51","doi-asserted-by":"publisher","unstructured":"Stamenkovic D, Karatzoglou A, Arapakis I, Xin X, Katevas K (2022) Choosing the best of both worlds: diverse and novel recommendations through multi-objective reinforcement learning. In: Candan KS, Liu H, Akoglu L, Dong XL, Tang J (eds) WSDM \u201922: the fifteenth ACM international conference on web search and data mining, virtual event\/Tempe, February 21\u201325, 2022, pp 957\u2013965. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3488560.3498471","DOI":"10.1145\/3488560.3498471"},{"key":"2455_CR52","doi-asserted-by":"publisher","unstructured":"Gong S, Zhu KQ (2022) Positive, negative and neutral: modeling implicit feedback in session-based news recommendation. In: Amig\u00f3 E, Castells P, Gonzalo J, Carterette B, Culpepper JS, Kazai G (eds) SIGIR \u201922: the 45th international ACM SIGIR conference on research and development in information retrieval, Madrid, Spain, July 11\u201315, 2022, pp 1185\u20131195. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3477495.3532040","DOI":"10.1145\/3477495.3532040"},{"issue":"1\u20132","key":"2455_CR53","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1007\/S10462-007-9023-8","volume":"25","author":"JP Kelly","year":"2006","unstructured":"Kelly JP, Bridge DG (2006) Enhancing the diversity of conversational collaborative recommendations: a comparison. Artif Intell Rev 25(1\u20132):79\u201395. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/S10462-007-9023-8","journal-title":"Artif Intell Rev"},{"key":"2455_CR54","unstructured":"Zhang S, Sutton RS (2017) A deeper look at experience replay. CoRR abs\/1712.01275"},{"key":"2455_CR55","unstructured":"Schaul T, Quan J, Antonoglou I, Silver D (2016) Prioritized experience replay"},{"key":"2455_CR56","doi-asserted-by":"publisher","unstructured":"An M, Wu F, Wu C, Zhang K, Liu Z, Xie X (2019) Neural news recommendation with long- and short-term user representations. In: Korhonen A, Traum DR, M\u00e0rquez L (eds) Proceedings of the 57th conference of the association for computational linguistics, ACL 2019, Florence, Italy, July 28\u2013August 2, 2019, volume 1: long papers, pp 336\u2013345. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.18653\/V1\/P19-1033","DOI":"10.18653\/V1\/P19-1033"},{"key":"2455_CR57","doi-asserted-by":"publisher","unstructured":"Xiang L, Yuan Q, Zhao S, Chen L, Zhang X, Yang Q, Sun J (2010) Temporal recommendation on graphs via long- and short-term preference fusion. In: Rao B, Krishnapuram B, Tomkins A, Yang Q (eds) Proceedings of the 16th ACM SIGKDD international conference on knowledge discovery and data mining, Washington, DC, USA, July 25\u201328, 2010, pp 723\u2013732. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/1835804.1835896","DOI":"10.1145\/1835804.1835896"},{"key":"2455_CR58","doi-asserted-by":"publisher","unstructured":"Sun K, Qian T, Chen T, Liang Y, Nguyen QVH, Yin H (2020) Where to go next: modeling long- and short-term user preferences for point-of-interest recommendation. In: The thirty-fourth AAAI conference on artificial intelligence, AAAI 2020, the thirty-second innovative applications of artificial intelligence conference, IAAI 2020, the tenth AAAI symposium on educational advances in artificial intelligence, EAAI 2020, New York, February 7\u201312, 2020, pp 214\u2013221. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1609\/AAAI.V34I01.5353","DOI":"10.1609\/AAAI.V34I01.5353"},{"key":"2455_CR59","doi-asserted-by":"publisher","unstructured":"Devooght R, Bersini H (2017) Long and short-term recommendations with recurrent neural networks. In: Bielikov\u00e1 M, Herder E, Cena F, Desmarais MC (eds) Proceedings of the 25th conference on user modeling, adaptation and personalization, UMAP 2017, Bratislava, Slovakia, July 09\u201312, 2017, pp 13\u201321. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3079628.3079670","DOI":"10.1145\/3079628.3079670"},{"issue":"5","key":"2455_CR60","doi-asserted-by":"publisher","first-page":"2512","DOI":"10.1109\/TKDE.2020.3007194","volume":"34","author":"P Zhao","year":"2022","unstructured":"Zhao P, Luo A, Liu Y, Xu J, Li Z, Zhuang F, Sheng VS, Zhou X (2022) Where to go next: a spatio-temporal gated network for next POI recommendation. IEEE Trans Knowl Data Eng 34(5):2512\u20132524. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1109\/TKDE.2020.3007194","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2455_CR61","doi-asserted-by":"publisher","unstructured":"Schlichtkrull MS, Kipf TN, Bloem P, Berg R, Titov I, Welling M (2018) Modeling relational data with graph convolutional networks. In: Gangemi A, Navigli R, Vidal M, Hitzler P, Troncy R, Hollink L, Tordai A, Alam M (eds) The semantic web-15th international conference, ESWC 2018, Heraklion, Crete, Greece, June 3\u20137, 2018, proceedings. Lecture Notes in Computer Science, vol 10843, pp 593\u2013607. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/978-3-319-93417-4_38","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"2455_CR62","unstructured":"Chen Y, Wu L, Zaki MJ (2020) Iterative deep graph learning for graph neural networks: better and robust node embeddings"},{"key":"2455_CR63","unstructured":"Chen Y, Wu L, Zaki MJ (2019) Reinforcement learning based graph-to-sequence model for natural question generation. CoRR abs\/1908.04942"},{"key":"2455_CR64","doi-asserted-by":"publisher","unstructured":"Wang X, Jin H, Zhang A, He X, Xu T, Chua T (2020) Disentangled graph collaborative filtering. In: Huang JX, Chang Y, Cheng X, Kamps J, Murdock V, Wen J, Liu Y (eds) Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval, SIGIR 2020, virtual Event, China, July 25\u201330, 2020, pp 1001\u20131010. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/3397271.3401137","DOI":"10.1145\/3397271.3401137"},{"key":"2455_CR65","unstructured":"Sabour S, Frosst N, Hinton GE (2017) Dynamic routing between capsules, pp 3856\u20133866"},{"key":"2455_CR66","unstructured":"Wang Z, Schaul T, Hessel M, Hasselt H, Lanctot M, Freitas N (2016) Dueling network architectures for deep reinforcement learning. In: Balcan M, Weinberger KQ (eds) Proceedings of the 33nd international conference on machine learning, ICML 2016, New York City, NY, USA, June 19\u201324, 2016. JMLR Workshop and Conference Proceedings, vol 48, pp 1995\u20132003"},{"issue":"3","key":"2455_CR67","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1109\/TIT.1957.1057416","volume":"3","author":"R Bellman","year":"1957","unstructured":"Bellman R, Kalaba R (1957) On the role of dynamic programming in statistical communication theory. IRE Trans Inf Theory 3(3):197\u2013203. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1109\/TIT.1957.1057416","journal-title":"IRE Trans Inf Theory"},{"issue":"3","key":"2455_CR68","doi-asserted-by":"publisher","first-page":"538","DOI":"10.1016\/S0022-5223(19)35778-2","volume":"95","author":"TJ Vander Salm","year":"1988","unstructured":"Vander Salm TJ, Ansell JE, Okike O, Marsicano TH, Lew R, Stephenson WP, Rooney K (1988) The role of epsilon-aminocaproic acid in reducing bleeding after cardiac operation: a double-blind randomized study. J Thorac Cardiovasc Surg 95(3):538\u2013540","journal-title":"J Thorac Cardiovasc Surg"},{"issue":"12","key":"2455_CR69","doi-asserted-by":"publisher","first-page":"15995","DOI":"10.1007\/s10854-021-06150-8","volume":"32","author":"M Liu","year":"2021","unstructured":"Liu M, Lan X, Zhang H, Xie P, Wu N, Yuan H, Sui K, Fan R, Liu C (2021) Iron\/epoxy random metamaterials with adjustable epsilon-near-zero and epsilon-negative property. J Mater Sci Mater Electron 32(12):15995\u201316007","journal-title":"J Mater Sci Mater Electron"},{"key":"2455_CR70","doi-asserted-by":"crossref","unstructured":"Zhang K, Yang Z, Ba\u015far T (2021) Multi-agent reinforcement learning: a selective overview of theories and algorithms. In: Handbook of reinforcement learning and control, pp 321\u2013384","DOI":"10.1007\/978-3-030-60990-0_12"},{"issue":"11","key":"2455_CR71","doi-asserted-by":"publisher","first-page":"13677","DOI":"10.1007\/s10489-022-04105-y","volume":"53","author":"A Oroojlooy","year":"2023","unstructured":"Oroojlooy A, Hajinezhad D (2023) A review of cooperative multi-agent deep reinforcement learning. Appl Intell 53(11):13677\u201313722. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/s10489-022-04105-y","journal-title":"Appl Intell"},{"key":"2455_CR72","unstructured":"Bordes A, Usunier N, Garc\u00eda-Dur\u00e1n A, Weston J, Yakhnenko O (2013) Translating embeddings for modeling multi-relational data, pp 2787\u20132795"},{"key":"2455_CR73","doi-asserted-by":"publisher","unstructured":"Han X, Cao S, Lv X, Lin Y, Liu Z, Sun M, Li J (2018) Openke: an open toolkit for knowledge embedding, pp 139\u2013144. https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.18653\/V1\/D18-2024","DOI":"10.18653\/V1\/D18-2024"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/link.springer.com\/content\/pdf\/10.1007\/s10115-025-02455-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/link.springer.com\/article\/10.1007\/s10115-025-02455-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/link.springer.com\/content\/pdf\/10.1007\/s10115-025-02455-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T15:19:18Z","timestamp":1757171958000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/link.springer.com\/10.1007\/s10115-025-02455-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,22]]},"references-count":74,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["2455"],"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/s10115-025-02455-w","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-4692909\/v1","asserted-by":"object"}]},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,22]]},"assertion":[{"value":"5 July 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 April 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 April 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 May 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This research does not involve human participants or pose potential harm to individuals. As such, formal ethical approval was not required. However, we would like to emphasize our commitment to ethical research practices and confirm that the study adheres to the ethical guidelines and principles set forth in the Springer Code of Ethics.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}}]}}