{"id":"https://openalex.org/W4312756395","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892118","title":"$(\\alpha,\\ \\beta)$-AWCS: $(\\alpha,\\ \\beta)$-Attributed Weighted Community Search on Bipartite Graphs","display_name":"$(\\alpha,\\ \\beta)$-AWCS: $(\\alpha,\\ \\beta)$-Attributed Weighted Community Search on Bipartite Graphs","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312756395","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892118"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892118","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":"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/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":true,"raw_author_name":"Dengshi Li","raw_affiliation_strings":["School of Artificial Intelligence, Jianghan University,Wuhan,China,430056"],"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/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"],"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"],"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/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"],"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/A5100401912","display_name":"Xiaochen Wang","orcid":"https://orcid.org/0000-0001-9467-6797"},"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":"Xiaochen Wang","raw_affiliation_strings":["School of Computer Science, Wuhan University,Wuhan,China,430072"],"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":5,"corresponding_author_ids":["https://openalex.org/A5055698842"],"corresponding_institution_ids":["https://openalex.org/I31590910"],"apc_list":null,"apc_paid":null,"fwci":0.8735,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.70660377,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9965999722480774,"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/T11478","display_name":"Caching and Content Delivery","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/bipartite-graph","display_name":"Bipartite graph","score":0.7767997980117798},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.574439525604248},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4791671335697174},{"id":"https://openalex.org/keywords/alpha","display_name":"Alpha (finance)","score":0.4110335409641266},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.4008038640022278},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.36800193786621094},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3668200969696045},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3504539728164673},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31769973039627075},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29689469933509827},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.09512913227081299},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09166967868804932}],"concepts":[{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.7767997980117798},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.574439525604248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4791671335697174},{"id":"https://openalex.org/C64943373","wikidata":"https://www.wikidata.org/wiki/Q2651003","display_name":"Alpha (finance)","level":4,"score":0.4110335409641266},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.4008038640022278},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.36800193786621094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3668200969696045},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3504539728164673},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31769973039627075},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29689469933509827},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.09512913227081299},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09166967868804932},{"id":"https://openalex.org/C171606756","wikidata":"https://www.wikidata.org/wiki/Q506132","display_name":"Psychometrics","level":2,"score":0.0},{"id":"https://openalex.org/C49453240","wikidata":"https://www.wikidata.org/wiki/Q1592163","display_name":"Construct validity","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892118","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":[{"score":0.5899999737739563,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G5379492266","display_name":null,"funder_award_id":"61701194","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8650790963","display_name":null,"funder_award_id":"2019029","funder_id":"https://openalex.org/F4320326959","funder_display_name":"Jianghan University"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326959","display_name":"Jianghan University","ror":"https://ror.org/041c9x778"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W85648037","https://openalex.org/W248604449","https://openalex.org/W2066780923","https://openalex.org/W2127048411","https://openalex.org/W2547646153","https://openalex.org/W2594188495","https://openalex.org/W2621145626","https://openalex.org/W2759385412","https://openalex.org/W2962788915","https://openalex.org/W3009094743","https://openalex.org/W3093301018","https://openalex.org/W3101347651","https://openalex.org/W3102641634","https://openalex.org/W4246662059"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2371352078","https://openalex.org/W2953461625","https://openalex.org/W2077383796","https://openalex.org/W4390409907","https://openalex.org/W3085245180","https://openalex.org/W2586280130","https://openalex.org/W4221143622","https://openalex.org/W1981723335","https://openalex.org/W3111310291"],"abstract_inverted_index":{"Community":[0,128],"search":[1,191],"on":[2,250],"bipartite":[3],"graphs":[4],"aims":[5],"to":[6,42,59,178,272],"find":[7],"a":[8,119,140,175,211],"community":[9,25],"closely":[10],"associated":[11],"with":[12,234],"the":[13,29,33,40,44,47,53,64,94,109,113,148,190,197,201,206,219,232,235,240,263,273],"query":[14,149,185],"vertex":[15,71,83,233],"for":[16,108,121],"personalized":[17],"recommendation,":[18],"fraud":[19],"detection,":[20],"and":[21,32,78,163,193,216],"team":[22],"formation.":[23],"During":[24],"search,":[26],"considering":[27],"both":[28,153,259],"structural":[30,61,241,277],"closeness":[31],"homogeneity":[34],"of":[35,37,46,63,68,80,96,104,143,200,205,213,253],"attributes":[36,95,198],"nodes":[38,65],"is":[39,72,84],"key":[41],"improving":[43],"quality":[45],"output":[48,114,139,202],"community.":[49,115,203],"Traditional":[50],"work":[51],"uses":[52],"<tex":[54,75,87,122,131,144,158],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[55,76,88,123,132,145,159],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$(\\alpha,\\beta)$</tex>":[56],"-core":[57],"model":[58],"guarantee":[60],"cohesion":[62,215,242,278],"(i.e.,":[66,156,166],"degree":[67,79],"each":[69,81],"upper":[70],"at":[73,85],"least":[74,86],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\alpha$</tex>":[77],"lower":[82],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\beta$</tex>":[89],").":[90],"However,":[91],"it":[92],"ignores":[93],"nodes,":[97],"resulting":[98],"in":[99,112],"an":[100],"average":[101],"attribute":[102,214,237,264],"similarity":[103],"only":[105],"about":[106],"0.17":[107],"node":[110],"pairs":[111],"In":[116],"this":[117],"paper,":[118],"framework":[120,173],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$(\\alpha,\\":[124,133,160],"\\beta)$</tex>":[125,134],"-Attributed":[126],"Weighted":[127],"Search":[129],"(":[130,157],"-AWCS)":[135],"was":[136,279],"proposed.":[137],"It":[138],"connected":[141],"subgraph":[142,212],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$G$</tex>":[146],"containing":[147],"vertex,":[150],"which":[151,229],"satisfies":[152],"structurally":[154],"cohesive":[155],"\\beta){-}$</tex>":[161],"-core)":[162],"keyword":[164],"cohesiveness":[165,199,265],"its":[167],"vertices":[168,180],"share":[169],"common":[170],"keywords).":[171],"The":[172,222],"includes":[174],"pruning":[176],"strategy":[177],"strip":[179],"that":[181,258],"do":[182],"not":[183],"contain":[184],"attributes,":[186],"thus":[187],"effectively":[188],"reducing":[189],"space,":[192],"two":[194],"algorithms":[195,208,260],"improve":[196,262],"One":[204],"exact":[207],"first":[209],"obtains":[210],"subsequently":[217],"keeps":[218],"structure":[220],"cohesive.":[221],"other":[223],"approximate":[224],"algorithm":[225],"has":[226],"higher":[227],"robustness,":[228],"iteratively":[230],"removes":[231],"lowest":[236],"score":[238],"until":[239],"cannot":[243],"be":[244],"maintained.":[245],"We":[246],"have":[247],"conducted":[248],"experiments":[249],"real":[251],"datasets":[252],"different":[254],"sizes.":[255],"Experiments":[256],"show":[257],"can":[261],"metric":[266],"by":[267],"more":[268],"than":[269],"25%":[270],"compared":[271],"traditional":[274],"method.":[275],"Meanwhile,":[276],"appropriate.":[280]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
