{"id":"https://openalex.org/W4376607800","doi":"https://doi.org/10.1109/tcss.2023.3272331","title":"ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning","display_name":"ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning","publication_year":2023,"publication_date":"2023-05-15","ids":{"openalex":"https://openalex.org/W4376607800","doi":"https://doi.org/10.1109/tcss.2023.3272331"},"language":"en","primary_location":{"id":"doi:10.1109/tcss.2023.3272331","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2023.3272331","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Social Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060325185","display_name":"Tiantian Chen","orcid":"https://orcid.org/0000-0003-3513-6170"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tiantian Chen","raw_affiliation_strings":["Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA"],"raw_orcid":"https://orcid.org/0000-0003-3513-6170","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030184040","display_name":"Siwen Yan","orcid":"https://orcid.org/0000-0003-1706-2921"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siwen Yan","raw_affiliation_strings":["Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA"],"raw_orcid":"https://orcid.org/0000-0003-1706-2921","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028160889","display_name":"Jianxiong Guo","orcid":"https://orcid.org/0000-0002-0994-3297"},"institutions":[{"id":"https://openalex.org/I12615008","display_name":"Beijing Normal-Hong Kong Baptist University","ror":"https://ror.org/04snvc712","country_code":"CN","type":"education","lineage":["https://openalex.org/I12615008"]},{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxiong Guo","raw_affiliation_strings":["Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai, China","Guangdong Key Laboratory of AI and Multi-Modal Data Processing, BNU-HKBU United International College, Zhuhai, China"],"raw_orcid":"https://orcid.org/0000-0002-0994-3297","affiliations":[{"raw_affiliation_string":"Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"Guangdong Key Laboratory of AI and Multi-Modal Data Processing, BNU-HKBU United International College, Zhuhai, China","institution_ids":["https://openalex.org/I12615008"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070037321","display_name":"Weili Wu","orcid":"https://orcid.org/0000-0001-8747-6340"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weili Wu","raw_affiliation_strings":["Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA"],"raw_orcid":"https://orcid.org/0000-0001-8747-6340","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":14.0199,"has_fulltext":false,"cited_by_count":87,"citation_normalized_percentile":{"value":0.99239048,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"11","issue":"2","first_page":"2210","last_page":"2221"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9595999717712402,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9544000029563904,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7237236499786377},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.7125342488288879},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6146528720855713},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.580542266368866},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5233206748962402},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5198257565498352},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46189936995506287},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45041367411613464},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4487687945365906},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4365329146385193},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.40505385398864746},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3847798705101013},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2309103012084961}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7237236499786377},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.7125342488288879},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6146528720855713},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.580542266368866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5233206748962402},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5198257565498352},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46189936995506287},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45041367411613464},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4487687945365906},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4365329146385193},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.40505385398864746},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3847798705101013},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2309103012084961},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcss.2023.3272331","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2023.3272331","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Social Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5381427449","display_name":null,"funder_award_id":"62202055","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7784844501","display_name":"SPX: Collaborative Research: Enabling Efficient Computer Architectural and System Support for Next-Generation Network Function Virtualization","funder_award_id":"1822985","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7950295864","display_name":"III: Small: Collaborative Research: Stream-Based Active Mining at Scale: Non-Linear Non-Submodular Maximization","funder_award_id":"1907472","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W166862392","https://openalex.org/W1984069252","https://openalex.org/W2005179971","https://openalex.org/W2035165116","https://openalex.org/W2061820396","https://openalex.org/W2108278206","https://openalex.org/W2132801025","https://openalex.org/W2145339207","https://openalex.org/W2160411082","https://openalex.org/W2294347342","https://openalex.org/W2396832258","https://openalex.org/W2607264901","https://openalex.org/W2746553466","https://openalex.org/W2755088640","https://openalex.org/W2795034086","https://openalex.org/W2798654119","https://openalex.org/W2910911697","https://openalex.org/W2949549477","https://openalex.org/W2962887179","https://openalex.org/W3001111845","https://openalex.org/W3028110392","https://openalex.org/W3029231733","https://openalex.org/W3047863327","https://openalex.org/W3081235889","https://openalex.org/W3144753569","https://openalex.org/W3152893301","https://openalex.org/W3170112077","https://openalex.org/W4214717370","https://openalex.org/W4225396469","https://openalex.org/W4285195085","https://openalex.org/W4312656781","https://openalex.org/W6697873463","https://openalex.org/W6748632789","https://openalex.org/W6754582438","https://openalex.org/W6763761351","https://openalex.org/W6773092609","https://openalex.org/W6782992894","https://openalex.org/W6785948369","https://openalex.org/W6797083137","https://openalex.org/W6838220758"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W4306904969","https://openalex.org/W3162204513","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4380318855","https://openalex.org/W3084456289","https://openalex.org/W2024136090","https://openalex.org/W4391331176","https://openalex.org/W2263596235"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"selecting":[2],"a":[3,32,110,198,235],"small":[4,193,199],"subset":[5],"of":[6,79,91,163,179,238,253],"nodes":[7],"with":[8,45,75,156,197],"maximum":[9],"influence":[10,14,29],"on":[11,96,161,171,191,203,224,240],"networks,":[12],"the":[13,28,35,72,76,118,153,164,172,177,249],"maximization":[15],"(IM)":[16],"problem":[17,120,155],"has":[18],"been":[19,94],"extensively":[20],"studied.":[21],"Since":[22],"it":[23,60],"is":[24,189],"#P-hard":[25],"to":[26,62,64,99,116,151,217],"compute":[27],"spread":[30],"given":[31],"seed":[33],"set,":[34],"state-of-the-art":[36],"methods,":[37],"including":[38],"heuristic":[39],"and":[40,55,67,87,135,167,201,219,227,242,245,251],"approximation":[41],"algorithms,":[42],"are":[43],"faced":[44],"great":[46],"difficulties":[47],"such":[48],"as":[49],"theoretical":[50],"guarantee,":[51],"time":[52],"efficiency,":[53],"generalization,":[54],"so":[56],"on.":[57],"This":[58],"makes":[59,176],"unable":[61],"adapt":[63],"large-scale":[65],"networks":[66,130,206],"more":[68],"complex":[69],"applications.":[70],"On":[71],"other":[73,88],"side,":[74],"latest":[77],"achievements":[78],"deep":[80,137],"reinforcement":[81],"learning":[82],"(DRL)":[83],"in":[84,121],"artificial":[85],"intelligence":[86],"fields,":[89],"lots":[90],"work":[92],"have":[93],"focused":[95],"exploiting":[97],"DRL":[98,113,157],"solve":[100,152],"combinatorial":[101],"optimization":[102],"(CO)":[103],"problems.":[104],"Inspired":[105],"by":[106],"this,":[107],"we":[108,233],"propose":[109],"novel":[111],"end-to-end":[112],"framework,":[114],"ToupleGDD,":[115],"address":[117],"IM":[119,154],"this":[122],"article,":[123],"which":[124,175,211],"incorporates":[125],"three":[126],"coupled":[127],"graph":[128],"neural":[129],"(GNNs)":[131],"for":[132,146],"network":[133,166],"embedding":[134],"double":[136],"<inline-formula":[138],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[139],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[140],"<tex-math":[141],"notation=\"LaTeX\">$Q$":[142],"</tex-math></inline-formula>":[143],"-networks":[144],"(DQNs)":[145],"parameters":[147],"learning.":[148],"Previous":[149],"efforts":[150],"trained":[158,190],"their":[159,180],"models":[160,181],"subgraphs":[162],"whole":[165,173],"then":[168],"tested":[169,202],"them":[170],"graph,":[174],"performance":[178],"unstable":[182],"among":[183],"different":[184,205],"networks.":[185],"However,":[186],"our":[187,254],"model":[188],"several":[192,225],"randomly":[194],"generated":[195],"graphs":[196],"budget":[200],"completely":[204],"under":[207],"various":[208],"large":[209,236],"budgets,":[210],"can":[212],"obtain":[213],"results":[214,221,247],"very":[215],"close":[216],"IMM":[218],"better":[220],"than":[222],"OPIM-C":[223],"datasets":[226,244],"shows":[228],"strong":[229],"generalization":[230],"ability.":[231],"Finally,":[232],"conduct":[234],"number":[237],"experiments":[239],"synthetic":[241],"realistic":[243],"experimental":[246],"prove":[248],"effectiveness":[250],"superiority":[252],"model.":[255]},"counts_by_year":[{"year":2026,"cited_by_count":18},{"year":2025,"cited_by_count":40},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":6}],"updated_date":"2026-06-27T08:28:00.272161","created_date":"2023-05-17T00:00:00"}