{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T08:50:26Z","timestamp":1775551826249,"version":"3.50.1"},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["625B2163"],"award-info":[{"award-number":["625B2163"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Artificial Intelligence"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.artint.2026.104500","type":"journal-article","created":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T00:08:35Z","timestamp":1772150915000},"page":"104500","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Exploring multi-layered networks through random walks: bridging offline optimization and online learning"],"prefix":"10.1016","volume":"354","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0179-196X","authenticated-orcid":false,"given":"Xiangxiang","family":"Dai","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8628-5873","authenticated-orcid":false,"given":"Xutong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9557-3551","authenticated-orcid":false,"given":"Jinhang","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7885-7069","authenticated-orcid":false,"given":"Xiaowei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0065-3610","authenticated-orcid":false,"given":"Wei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7466-0384","authenticated-orcid":false,"given":"John C S","family":"Lui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.artint.2026.104500_bib0001","series-title":"Proceedings of the 16th International Conference on Supercomputing","first-page":"84","article-title":"Search and replication in unstructured peer-to-peer networks","author":"Lv","year":"2002"},{"key":"10.1016\/j.artint.2026.104500_bib0002","series-title":"Pagerank beyond the web","first-page":"321","volume":"57","author":"Gleich","year":"2015"},{"key":"10.1016\/j.artint.2026.104500_bib0003","series-title":"Thirty-Second AAAI Conference on Artificial Intelligence","article-title":"Maximizing influence in an unknown social network","author":"Wilder","year":"2018"},{"issue":"5","key":"10.1016\/j.artint.2026.104500_bib0004","first-page":"4570","article-title":"Common neighbors matter: fast random walk sampling with common neighbor awareness","volume":"35","author":"Wang","year":"2022","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.artint.2026.104500_bib0005","unstructured":"K. Lerman, L. Jones, Social browsing on flickr, arXiv preprint:cs\/0612047."},{"issue":"12","key":"10.1016\/j.artint.2026.104500_bib0006","doi-asserted-by":"crossref","first-page":"7825","DOI":"10.1109\/TKDE.2024.3423442","article-title":"Conversational recommendation with online learning and clustering on misspecified users","volume":"36","author":"Dai","year":"2024","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"1","key":"10.1016\/j.artint.2026.104500_bib0007","first-page":"1746","article-title":"Combinatorial multi-armed bandit and its extension to probabilistically triggered arms","volume":"17","author":"Chen","year":"2016","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.artint.2026.104500_bib0008","series-title":"IEEE 35th International Conference on Data Engineering (ICDE)","first-page":"962","article-title":"Walking with perception: efficient random walk sampling via common neighbor awareness","author":"Li","year":"2019"},{"key":"10.1016\/j.artint.2026.104500_bib0009","series-title":"Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"137","article-title":"Maximizing the spread of influence through a social network","author":"Kempe","year":"2003"},{"key":"10.1016\/j.artint.2026.104500_bib0010","series-title":"Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"199","article-title":"Efficient influence maximization in social networks","author":"Chen","year":"2009"},{"issue":"3","key":"10.1016\/j.artint.2026.104500_bib0011","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1007\/s10618-012-0262-1","article-title":"Scalable influence maximization for independent cascade model in large-scale social networks","volume":"25","author":"Wang","year":"2012","journal-title":"Data Min. Knowl. Discov."},{"key":"10.1016\/j.artint.2026.104500_bib0012","series-title":"Proceedings of the 21st International Conference on World Wide Web","first-page":"381","article-title":"Optimizing budget allocation among channels and influencers","author":"Alon","year":"2012"},{"key":"10.1016\/j.artint.2026.104500_bib0013","series-title":"International Conference on Machine Learning","first-page":"351","article-title":"Optimal budget allocation: th eoretical guarantee and efficient algorithm","author":"Soma","year":"2014"},{"issue":"5","key":"10.1016\/j.artint.2026.104500_bib0014","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1090\/S0002-9904-1952-09620-8","article-title":"Some aspects of the sequential design of experiments","volume":"58","author":"Robbins","year":"1952","journal-title":"Bull. Am. Math. Soc."},{"issue":"1","key":"10.1016\/j.artint.2026.104500_bib0015","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000024","article-title":"Regret analysis of stochastic and nonstochastic multi-armed bandit problems","volume":"5","author":"Bubeck","year":"2012","journal-title":"Found. Trend.\u00aeMach. Learn."},{"issue":"5","key":"10.1016\/j.artint.2026.104500_bib0016","doi-asserted-by":"crossref","first-page":"1466","DOI":"10.1109\/TNET.2011.2181864","article-title":"Combinatorial network optimization with unknown variables: multi-armed bandits with linear rewards and individual observations","volume":"20","author":"Gai","year":"2012","journal-title":"IEEE\/ACM Transact. Network.(TON)"},{"key":"10.1016\/j.artint.2026.104500_bib0017","series-title":"Advances in Neural Information Processing Systems","first-page":"1161","article-title":"Improving regret bounds for combinatorial semi-bandits with probabilistically triggered arms and its applications","author":"Wang","year":"2017"},{"key":"10.1016\/j.artint.2026.104500_bib0018","series-title":"Advances in Neural Information Processing Systems","first-page":"5474","article-title":"Community exploration: from offline optimization to online learning","author":"Chen","year":"2018"},{"key":"10.1016\/j.artint.2026.104500_bib0019","series-title":"International Conference on Machine Learning","first-page":"7057","article-title":"Multi-layered network exploration via random walks: from offline optimization to online learning","author":"Liu","year":"2021"},{"key":"10.1016\/j.artint.2026.104500_bib0020","series-title":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V","first-page":"427","article-title":"A unified online-offline framework for co-branding campaign recommendations","author":"Dai","year":"2025"},{"key":"10.1016\/j.artint.2026.104500_bib0021","series-title":"Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms","first-page":"1216","article-title":"Online submodular welfare maximization: greedy is optimal","author":"Kapralov","year":"2013"},{"key":"10.1016\/j.artint.2026.104500_bib0022","series-title":"Advances in Neural Information Processing Systems","first-page":"847","article-title":"A generalization of submodular cover via the diminishing return property on the integer lattice","author":"Soma","year":"2015"},{"issue":"3","key":"10.1016\/j.artint.2026.104500_bib0023","doi-asserted-by":"crossref","first-page":"982","DOI":"10.1109\/TON.2024.3519568","article-title":"Variance-aware bandit framework for dynamic probabilistic maximum coverage problem with triggered or self-reliant arms","volume":"33","author":"Dai","year":"2025","journal-title":"IEEE Transact. Network."},{"key":"10.1016\/j.artint.2026.104500_bib0024","series-title":"ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems","first-page":"112","article-title":"Combinatorial logistic bandits, in: abstracts of the 2025","author":"Liu","year":"2025"},{"issue":"1","key":"10.1016\/j.artint.2026.104500_bib0025","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/S0020-0190(99)00031-9","article-title":"The budgeted maximum coverage problem","volume":"70","author":"Khuller","year":"1999","journal-title":"Inf. Process. Lett."},{"key":"10.1016\/j.artint.2026.104500_bib0026","series-title":"International Conference on Machine Learning","first-page":"38251","article-title":"Offline learning for combinatorial multi-armed bandits","author":"Liu","year":"2025"},{"key":"10.1016\/j.artint.2026.104500_bib0027","series-title":"Conference on Learning Theory","first-page":"2830","article-title":"Tight lower bounds for combinatorial multi-armed bandits","author":"Merlis","year":"2020"},{"key":"10.1016\/j.artint.2026.104500_bib0028","first-page":"14904","article-title":"Batch-size independent regret bounds for combinatorial semi-bandits with probabilistically triggered arms or independent arms","volume":"35","author":"Liu","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.artint.2026.104500_bib0029","series-title":"International Conference on Machine Learning","first-page":"5114","article-title":"Thompson sampling for combinatorial semi-bandits","author":"Wang","year":"2018"},{"key":"10.1016\/j.artint.2026.104500_bib0030","series-title":"Multilayer Social Networks","author":"Dickison","year":"2016"},{"issue":"4","key":"10.1016\/j.artint.2026.104500_bib0031","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1145\/964725.633039","article-title":"Measuring isp topologies with rocketfuel,","volume":"32","author":"Spring","year":"2002","journal-title":"ACM SIGCOMM Comput. Commun. Rev."},{"issue":"4","key":"10.1016\/j.artint.2026.104500_bib0032","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1734213.1734219","article-title":"Routing betweenness centrality","volume":"57","author":"Dolev","year":"2010","journal-title":"J. ACM (JACM)"},{"key":"10.1016\/j.artint.2026.104500_bib0033","series-title":"Markov Processes for Stochastic Modeling","volume":"6","author":"Kijima","year":"1997"},{"key":"10.1016\/j.artint.2026.104500_bib0034","series-title":"Basics of Applied Stochastic Processes","author":"Serfozo","year":"2009"},{"key":"10.1016\/j.artint.2026.104500_bib0035","article-title":"Concentration of measure inequalities in information theory, communications, and coding","volume":"10","author":"Raginsky","year":"2013","journal-title":"Foundat. Trends Commun. Inform. Theory"},{"issue":"6","key":"10.1016\/j.artint.2026.104500_bib0036","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1061\/(ASCE)0733-9496(2008)134:6(516)","article-title":"Efficient sensor placement optimization for securing large water distribution networks","volume":"134","author":"Krause","year":"2008","journal-title":"J. Water Resour. Plann. Manage."},{"key":"10.1016\/j.artint.2026.104500_bib0037","series-title":"Concentration of Measure for the Analysis of Randomized Algorithms","author":"Dubhashi","year":"2009"},{"issue":"19","key":"10.1016\/j.artint.2026.104500_bib0038","doi-asserted-by":"crossref","first-page":"1876","DOI":"10.1016\/j.tcs.2009.01.016","article-title":"Exploration-exploitation tradeoff using variance estimates in multi-armed bandits","volume":"410","author":"Audibert","year":"2009","journal-title":"Theor. Comput. Sci."},{"key":"10.1016\/j.artint.2026.104500_bib0039","series-title":"Conference on Learning Theory","first-page":"2465","article-title":"Batch-size independent regret bounds for the combinatorial multi-armed bandit problem","author":"Merlis","year":"2019"},{"key":"10.1016\/j.artint.2026.104500_bib0040","series-title":"International Conference on Machine Learning","first-page":"22559","article-title":"Contextual combinatorial bandits with probabilistically triggered arms","author":"Liu","year":"2023"}],"container-title":["Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0004370226000263?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0004370226000263?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T07:58:42Z","timestamp":1775548722000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0004370226000263"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":40,"alternative-id":["S0004370226000263"],"URL":"https:\/\/doi.org\/10.1016\/j.artint.2026.104500","relation":{},"ISSN":["0004-3702"],"issn-type":[{"value":"0004-3702","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Exploring multi-layered networks through random walks: bridging offline optimization and online learning","name":"articletitle","label":"Article Title"},{"value":"Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.artint.2026.104500","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"104500"}}