{"id":"https://openalex.org/W4236581180","doi":"https://doi.org/10.1109/asonam.2016.7752243","title":"Learning cascaded influence under partial monitoring","display_name":"Learning cascaded influence under partial monitoring","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W4236581180","doi":"https://doi.org/10.1109/asonam.2016.7752243"},"language":"en","primary_location":{"id":"doi:10.1109/asonam.2016.7752243","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam.2016.7752243","pdf_url":null,"source":{"id":"https://openalex.org/S4363608003","display_name":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","raw_type":"proceedings-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/A5100436760","display_name":"Jie Zhang","orcid":"https://orcid.org/0000-0002-5348-7671"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Zhang","raw_affiliation_strings":["Department of Physics, Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Department of Physics, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089063294","display_name":"Jiaqi Ma","orcid":"https://orcid.org/0000-0001-8292-5901"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Ma","raw_affiliation_strings":["Department of Automation, Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044791875","display_name":"Jie Tang","orcid":"https://orcid.org/0000-0003-3487-4593"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Tang","raw_affiliation_strings":["Department of Computer Science, Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100436760"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.52167929,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.66314399,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"13","issue":null,"first_page":"255","last_page":"262"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.998199999332428,"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/T11644","display_name":"Spam and Phishing Detection","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.7233319878578186},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5998260378837585},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4971330463886261},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4442669153213501},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34209489822387695},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33105194568634033}],"concepts":[{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.7233319878578186},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5998260378837585},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4971330463886261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4442669153213501},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34209489822387695},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33105194568634033},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asonam.2016.7752243","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam.2016.7752243","pdf_url":null,"source":{"id":"https://openalex.org/S4363608003","display_name":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W35251828","https://openalex.org/W874708728","https://openalex.org/W1440676288","https://openalex.org/W1510812122","https://openalex.org/W1578264931","https://openalex.org/W1856548066","https://openalex.org/W1987292194","https://openalex.org/W2022322548","https://openalex.org/W2033198212","https://openalex.org/W2042123098","https://openalex.org/W2046989790","https://openalex.org/W2056609785","https://openalex.org/W2061820396","https://openalex.org/W2073926352","https://openalex.org/W2077902449","https://openalex.org/W2092473613","https://openalex.org/W2107559689","https://openalex.org/W2109603058","https://openalex.org/W2122422466","https://openalex.org/W2152898676","https://openalex.org/W2156020699","https://openalex.org/W2168405694","https://openalex.org/W2183702177","https://openalex.org/W2406281999","https://openalex.org/W2914156981","https://openalex.org/W2963860006","https://openalex.org/W2964240248","https://openalex.org/W3084669832","https://openalex.org/W3104626960","https://openalex.org/W4242087913","https://openalex.org/W6601392155","https://openalex.org/W6623739785","https://openalex.org/W6630683246","https://openalex.org/W6634623812","https://openalex.org/W6636546920","https://openalex.org/W6677973377","https://openalex.org/W6680270882","https://openalex.org/W6684381734","https://openalex.org/W6714003741"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Social":[0],"influence":[1,30,36,52,71,173],"has":[2,24,37,94],"attracted":[3],"tremendous":[4],"attention":[5],"from":[6],"both":[7,135],"academic":[8],"and":[9,59,83,137,141,178],"industrial":[10],"communities":[11],"due":[12],"to":[13,85,174],"the":[14,28,47,55,69,73,103,127,159,170],"rapid":[15],"development":[16],"of":[17,49,99,105,117,155,164],"online":[18,64],"social":[19],"networks.":[20],"While":[21],"most":[22],"research":[23],"been":[25,39],"focused":[26],"on":[27,54,134],"direct":[29],"between":[31],"peers,":[32],"learning":[33,65,68],"cascaded":[34,70,172],"indirect":[35,51],"not":[38],"previously":[40],"studied.":[41],"In":[42],"this":[43,87],"paper,":[44],"we":[45,168],"formulate":[46],"concept":[48],"cascade":[50],"based":[53],"Independent":[56],"Cascade":[57],"model":[58],"then":[60],"propose":[61,78],"a":[62,95,114,120,188],"novel":[63],"algorithm":[66],"for":[67,194],"in":[72,123,162],"partial":[74],"monitoring":[75],"setting.":[76],"We":[77,89,108,125],"two":[79],"bandit":[80],"algorithms":[81,129,184],"E-EXP3":[82,93],"RE-EXP3":[84,148],"address":[86],"problem.":[88],"theoretically":[90],"prove":[91],"that":[92,112,147,181],"cumulative":[96],"regret":[97],"bound":[98],"O(\u221a(T))":[100],"over":[101],"T,":[102],"number":[104],"time":[106],"stamps.":[107],"will":[109],"also":[110],"show":[111,146,180],"RE-EXP3,":[113],"relaxed":[115],"version":[116],"E-EXP3,":[118],"achieves":[119],"better":[121],"performance":[122],"practice.":[124],"compare":[126],"proposed":[128,183],"with":[130],"three":[131],"baseline":[132],"methods":[133,161],"synthetic":[136],"real":[138],"networks":[139],"(Weibo":[140],"AMiner).":[142],"Our":[143],"experimental":[144],"results":[145],"converges":[149],"100\u00d7":[150],"faster":[151],"than":[152],"E-EXP3.":[153],"Both":[154],"them":[156],"significantly":[157],"outperform":[158],"alternative":[160],"terms":[163],"normalized":[165],"regret.":[166],"Finally,":[167],"apply":[169],"learned":[171],"help":[175,186],"behavior":[176,195],"prediction":[177],"experiments":[179],"our":[182],"can":[185],"achieve":[187],"significant":[189],"improvement":[190],"(10-15%":[191],"by":[192],"accuracy)":[193],"prediction.":[196]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}