{"id":"https://openalex.org/W3008120872","doi":"https://doi.org/10.1109/bigdata47090.2019.9005701","title":"MC<sup>2</sup>:Unsupervised Multiple Social Network Alignment","display_name":"MC<sup>2</sup>:Unsupervised Multiple Social Network Alignment","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3008120872","doi":"https://doi.org/10.1109/bigdata47090.2019.9005701","mag":"3008120872"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9005701","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9005701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","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/A5100357026","display_name":"Gen Li","orcid":"https://orcid.org/0000-0002-3666-3936"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gen Li","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100318687","display_name":"Li Sun","orcid":"https://orcid.org/0000-0003-4562-2279"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Sun","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101759820","display_name":"Zhongbao Zhang","orcid":"https://orcid.org/0000-0002-3242-150X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongbao Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041611917","display_name":"Pengxin Ji","orcid":"https://orcid.org/0009-0006-5383-6671"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengxin Ji","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036865453","display_name":"Sen Su","orcid":"https://orcid.org/0000-0003-4266-7527"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Su","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036357902","display_name":"Philip S. Yu","orcid":"https://orcid.org/0000-0002-3491-5968"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip S. Yu","raw_affiliation_strings":["University of Illinois at Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100357026"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.5792,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.67355607,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"9","issue":null,"first_page":"1151","last_page":"1156"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9987999796867371,"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.954800009727478,"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/computer-science","display_name":"Computer science","score":0.6724634170532227},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5873614549636841},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5263819694519043},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5224713087081909},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.498598575592041},{"id":"https://openalex.org/keywords/diagonal","display_name":"Diagonal","score":0.4364308714866638},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3876704275608063},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37337544560432434},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20023095607757568},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.08987307548522949},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.08635663986206055}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6724634170532227},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5873614549636841},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5263819694519043},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5224713087081909},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.498598575592041},{"id":"https://openalex.org/C130367717","wikidata":"https://www.wikidata.org/wiki/Q189791","display_name":"Diagonal","level":2,"score":0.4364308714866638},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3876704275608063},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37337544560432434},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20023095607757568},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.08987307548522949},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.08635663986206055},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9005701","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9005701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1496564895","https://openalex.org/W1692592558","https://openalex.org/W1980680715","https://openalex.org/W2047532797","https://openalex.org/W2055345291","https://openalex.org/W2058036501","https://openalex.org/W2135029798","https://openalex.org/W2340622084","https://openalex.org/W2374981910","https://openalex.org/W2519104997","https://openalex.org/W2572926828","https://openalex.org/W2733511975","https://openalex.org/W2740605635","https://openalex.org/W2788259657","https://openalex.org/W2793022729","https://openalex.org/W2808254354","https://openalex.org/W2896831016","https://openalex.org/W2896997271","https://openalex.org/W2904205492","https://openalex.org/W2964142522","https://openalex.org/W3037567775","https://openalex.org/W3143596294","https://openalex.org/W6629756402","https://openalex.org/W6662241857","https://openalex.org/W6680012447","https://openalex.org/W6731581786","https://openalex.org/W6748348311","https://openalex.org/W6779669310"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W2364594919","https://openalex.org/W2135584473","https://openalex.org/W1861706286","https://openalex.org/W2219338811","https://openalex.org/W2167092671","https://openalex.org/W2149583853","https://openalex.org/W2143002539","https://openalex.org/W2130386332","https://openalex.org/W1120847856"],"abstract_inverted_index":{"Social":[0],"network":[1,80],"alignment,":[2],"identifying":[3],"social":[4,12,31,63,79,118,148],"accounts":[5],"of":[6,21,53,57,76,92],"the":[7,47,51,74,121,143,152,177,186],"same":[8],"individual":[9],"across":[10,17],"different":[11,147],"networks,":[13],"shows":[14],"fundamental":[15],"importance":[16],"a":[18,88,138],"wide":[19],"spectrum":[20],"applications.":[22],"Individuals":[23],"more":[24],"often":[25],"than":[26],"not":[27],"join":[28],"in":[29,36,120,129],"multiple":[30,62,78,117],"networks":[32,64,119],"and":[33,115],"it":[34],"is":[35,112],"fact":[37],"intractable":[38],"or":[39],"even":[40],"impossible":[41],"to":[42,50,72,102,113,141],"acquiring":[43],"supervision":[44],"for":[45],"guiding":[46],"alignment.":[48,81],"However,":[49],"best":[52],"our":[54],"knowledge,":[55],"none":[56],"existing":[58],"methods":[59],"can":[60],"align":[61,116],"without":[65],"supervision.":[66],"In":[67],"this":[68,84],"paper,":[69],"we":[70,86,135,155,174],"propose":[71,87],"study":[73],"problem":[75],"unsupervised":[77,90,126],"To":[82,150],"address":[83,151],"problem,":[85],"novel":[89],"model":[91,183],"Matrix":[93],"factorization":[94],"with":[95],"diagonal":[96],"Cone":[97],"under":[98],"orthogonal":[99],"Constraint,":[100],"referred":[101],"as":[103],"MC":[104,130,179],"<sup":[105,131,180],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[106,132,181],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[107,133,182],".":[108],"Its":[109],"core":[110],"idea":[111],"embed":[114],"common":[122,144],"subspace":[123,145],"via":[124],"an":[125,158],"approach.":[127],"Specifically,":[128],"model,":[134],"first":[136],"design":[137,157],"matrix":[139],"optimization":[140],"infer":[142],"from":[146],"networks.":[149],"nonconvex":[153],"optimization,":[154],"then":[156],"efficient":[159],"alternating":[160],"algorithm":[161],"by":[162],"leveraging":[163],"its":[164],"inherent":[165],"functional":[166],"property.":[167],"Through":[168],"extensive":[169],"experiments":[170],"on":[171],"real-world":[172],"datasets,":[173],"demonstrate":[175],"that":[176],"proposed":[178],"significantly":[184],"outperforms":[185],"state-of-the-art":[187],"methods.":[188]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
