{"id":"https://openalex.org/W4312255410","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892552","title":"ITC: Influential-Truss Community Search","display_name":"ITC: Influential-Truss Community Search","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312255410","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892552"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892552","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5055698842","display_name":"Dengshi Li","orcid":"https://orcid.org/0000-0002-3349-8664"},"institutions":[{"id":"https://openalex.org/I31590910","display_name":"Jianghan University","ror":"https://ror.org/041c9x778","country_code":"CN","type":"education","lineage":["https://openalex.org/I31590910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dengshi Li","raw_affiliation_strings":["School of Artificial Intelligence, Jianghan University,Wuhan,China,430056"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Jianghan University,Wuhan,China,430056","institution_ids":["https://openalex.org/I31590910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022668636","display_name":"Lu Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I31590910","display_name":"Jianghan University","ror":"https://ror.org/041c9x778","country_code":"CN","type":"education","lineage":["https://openalex.org/I31590910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Zeng","raw_affiliation_strings":["School of Artificial Intelligence, Jianghan University,Wuhan,China,430056"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Jianghan University,Wuhan,China,430056","institution_ids":["https://openalex.org/I31590910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008406199","display_name":"Ruimin Hu","orcid":"https://orcid.org/0000-0002-5872-3872"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruimin Hu","raw_affiliation_strings":["School of Computer Science, Wuhan University,Wuhan,China,430072"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University,Wuhan,China,430072","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011000361","display_name":"Xiaocong Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I31590910","display_name":"Jianghan University","ror":"https://ror.org/041c9x778","country_code":"CN","type":"education","lineage":["https://openalex.org/I31590910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaocong Liang","raw_affiliation_strings":["School of Artificial Intelligence, Jianghan University,Wuhan,China,430056"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Jianghan University,Wuhan,China,430056","institution_ids":["https://openalex.org/I31590910"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005226015","display_name":"Yilong Zang","orcid":"https://orcid.org/0000-0001-8535-071X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilong Zang","raw_affiliation_strings":["School of Computer Science, Wuhan University,Wuhan,China,430072"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University,Wuhan,China,430072","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"e 69 2","issue":null,"first_page":"01","last_page":"08"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9724000096321106,"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"}},{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9513999819755554,"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/cohesion","display_name":"Cohesion (chemistry)","score":0.7472281455993652},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6477603912353516},{"id":"https://openalex.org/keywords/community-structure","display_name":"Community structure","score":0.5537126660346985},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5471602082252502},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.42155811190605164},{"id":"https://openalex.org/keywords/truss","display_name":"Truss","score":0.4123995900154114},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.376470685005188},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.33035874366760254},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22196340560913086},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.20089027285575867},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13536018133163452},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0996944010257721}],"concepts":[{"id":"https://openalex.org/C104054115","wikidata":"https://www.wikidata.org/wiki/Q216828","display_name":"Cohesion (chemistry)","level":2,"score":0.7472281455993652},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6477603912353516},{"id":"https://openalex.org/C133079900","wikidata":"https://www.wikidata.org/wiki/Q5155065","display_name":"Community structure","level":2,"score":0.5537126660346985},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5471602082252502},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.42155811190605164},{"id":"https://openalex.org/C173534245","wikidata":"https://www.wikidata.org/wiki/Q1328068","display_name":"Truss","level":2,"score":0.4123995900154114},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.376470685005188},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33035874366760254},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22196340560913086},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.20089027285575867},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13536018133163452},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0996944010257721},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892552","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W248604449","https://openalex.org/W776559747","https://openalex.org/W1578152639","https://openalex.org/W1964419312","https://openalex.org/W1971526329","https://openalex.org/W1984903982","https://openalex.org/W2037487875","https://openalex.org/W2054353417","https://openalex.org/W2067024384","https://openalex.org/W2095293504","https://openalex.org/W2125895010","https://openalex.org/W2127048411","https://openalex.org/W2148606255","https://openalex.org/W2149551808","https://openalex.org/W2475306032","https://openalex.org/W2621145626","https://openalex.org/W2753758798","https://openalex.org/W2884889240","https://openalex.org/W2963054764","https://openalex.org/W2977885717","https://openalex.org/W3046171781","https://openalex.org/W3102641634","https://openalex.org/W6674068858"],"related_works":["https://openalex.org/W2955404263","https://openalex.org/W2055188469","https://openalex.org/W2365888646","https://openalex.org/W4238655142","https://openalex.org/W2914493398","https://openalex.org/W2741416590","https://openalex.org/W2782859253","https://openalex.org/W2045864404","https://openalex.org/W252900523","https://openalex.org/W4206022723"],"abstract_inverted_index":{"Community":[0],"search":[1,19,76,89,108,183,218],"is":[2,104,154,170,223],"a":[3,7,12,122,126],"method":[4,153],"of":[5,25,63,74,202,211,221],"finding":[6],"com-munity":[8],"closely":[9],"related":[10],"to":[11,38,60,69,120,147],"query":[13,131,164,179],"node.":[14,165],"The":[15],"latest":[16],"influence":[17,30,36,47,81,94,115,185,197],"community":[18,27,52,75,88,93,101,107,114,142,192,196,217],"considers":[20],"both":[21],"the":[22,26,29,35,40,46,50,64,71,87,130,139,163,167,182,191,194,200,204,216,230],"structural":[23,111,135,175,205],"cohesion":[24,112,136,176],"and":[28,113,137],"between":[31],"nodes.":[32,180],"It":[33],"sets":[34],"threshold":[37,48],"constrain":[39],"output":[41,51,65],"community.":[42,66],"However,":[43],"artificially":[44,79],"setting":[45,80],"makes":[49],"too":[53,56],"large":[54],"or":[55],"small,":[57],"which":[58,133,156,172],"leads":[59],"low":[61,72],"accuracy":[62,73,219],"In":[67,96,145],"order":[68,146],"avoid":[70],"caused":[77],"by":[78,109,225],"thresh-old":[82],"constraints,":[83],"this":[84,97],"paper":[85],"studies":[86],"problem":[90],"based":[91],"on":[92,178,208],"score.":[95,116,144],"paper,":[98],"an":[99,150],"influence-truss":[100],"(ITC)":[102],"model":[103,118],"proposed":[105],"for":[106],"combining":[110],"This":[117],"aims":[119],"obtain":[121,148],"connected":[123],"subgraph":[124],"in":[125],"social":[127],"network":[128],"containing":[129],"node,":[132],"satisfies":[134,138],"subgraph's":[140],"maximum":[141],"in-fluence":[143],"ITC,":[149],"effective":[151],"pruning":[152],"proposed,":[155],"strips":[157],"other":[158],"nodes":[159],"far":[160],"away":[161],"from":[162],"Then,":[166,181],"ITCS":[168,222],"algorithm":[169],"designed,":[171],"firstly":[173],"imposes":[174],"constraints":[177],"community's":[184],"scores":[186],"are":[187],"iteratively":[188],"calculated":[189],"until":[190],"has":[193],"highest":[195],"score":[198],"under":[199],"condition":[201],"meeting":[203],"cohesion.":[206],"Experiments":[207],"real-world":[209],"networks":[210],"different":[212],"scales":[213],"show":[214],"that":[215],"index":[220],"improved":[224],"about":[226],"20%":[227],"compared":[228],"with":[229],"traditional":[231],"method.":[232]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
