{"id":"https://openalex.org/W3211225551","doi":"https://doi.org/10.1145/3459637.3482310","title":"Unsupervised Large-Scale Social Network Alignment via Cross Network Embedding","display_name":"Unsupervised Large-Scale Social Network Alignment via Cross Network Embedding","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3211225551","doi":"https://doi.org/10.1145/3459637.3482310","mag":"3211225551"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482310","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482310","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","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/A5008247889","display_name":"Zhehan Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhehan Liang","raw_affiliation_strings":["Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100767600","display_name":"Yu Rong","orcid":"https://orcid.org/0000-0001-7387-302X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Rong","raw_affiliation_strings":["Tencent AI Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047137615","display_name":"Chenxin Li","orcid":"https://orcid.org/0000-0002-6276-7712"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenxin Li","raw_affiliation_strings":["Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100410605","display_name":"Yunlong Zhang","orcid":"https://orcid.org/0000-0002-2447-9138"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunlong Zhang","raw_affiliation_strings":["Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100772804","display_name":"Yue Huang","orcid":"https://orcid.org/0000-0002-3913-9400"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Huang","raw_affiliation_strings":["Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005345630","display_name":"Tingyang Xu","orcid":"https://orcid.org/0000-0002-8487-9045"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingyang Xu","raw_affiliation_strings":["Tencent AI Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052820597","display_name":"Xinghao Ding","orcid":"https://orcid.org/0000-0003-2288-5287"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinghao Ding","raw_affiliation_strings":["Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068865316","display_name":"Junzhou Huang","orcid":"https://orcid.org/0000-0002-9548-1227"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junzhou Huang","raw_affiliation_strings":["Tencent AI Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5008247889"],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":2.8553,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.92325905,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1008","last_page":"1017"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9973999857902527,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.953000009059906,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.760259211063385},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6264400482177734},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.6040536165237427},{"id":"https://openalex.org/keywords/social-network-analysis","display_name":"Social network analysis","score":0.517632782459259},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.516985297203064},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.49983930587768555},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48426005244255066},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46512672305107117},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.4644119441509247},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.43718183040618896},{"id":"https://openalex.org/keywords/network-analysis","display_name":"Network analysis","score":0.4293964207172394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4092187285423279},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3572186231613159},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3563033938407898},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1637967824935913},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.10946923494338989},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1011691689491272}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.760259211063385},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6264400482177734},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.6040536165237427},{"id":"https://openalex.org/C114713312","wikidata":"https://www.wikidata.org/wiki/Q7551269","display_name":"Social network analysis","level":3,"score":0.517632782459259},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.516985297203064},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.49983930587768555},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48426005244255066},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46512672305107117},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.4644119441509247},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.43718183040618896},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.4293964207172394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4092187285423279},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3572186231613159},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3563033938407898},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1637967824935913},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.10946923494338989},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1011691689491272},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3459637.3482310","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482310","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W633744573","https://openalex.org/W812851569","https://openalex.org/W1982350890","https://openalex.org/W2021999013","https://openalex.org/W2033389579","https://openalex.org/W2075633077","https://openalex.org/W2084512390","https://openalex.org/W2131681506","https://openalex.org/W2142535891","https://openalex.org/W2143668817","https://openalex.org/W2151936673","https://openalex.org/W2154851992","https://openalex.org/W2187089797","https://openalex.org/W2241660235","https://openalex.org/W2339803498","https://openalex.org/W2374981910","https://openalex.org/W2391555403","https://openalex.org/W2393319904","https://openalex.org/W2415901874","https://openalex.org/W2514012150","https://openalex.org/W2560545764","https://openalex.org/W2571692900","https://openalex.org/W2572926828","https://openalex.org/W2598689838","https://openalex.org/W2620318602","https://openalex.org/W2788259657","https://openalex.org/W2793022729","https://openalex.org/W2808605874","https://openalex.org/W2888657195","https://openalex.org/W2890703109","https://openalex.org/W2896997271","https://openalex.org/W2907492528","https://openalex.org/W2931335216","https://openalex.org/W2962756421","https://openalex.org/W2962911247","https://openalex.org/W2964321699","https://openalex.org/W2964418074","https://openalex.org/W2970823238","https://openalex.org/W2982204955","https://openalex.org/W2983178467","https://openalex.org/W2997128522","https://openalex.org/W2999269676","https://openalex.org/W3008765623","https://openalex.org/W3046983129","https://openalex.org/W3081295916","https://openalex.org/W3082217026","https://openalex.org/W3099768174","https://openalex.org/W3103296165","https://openalex.org/W3104097132","https://openalex.org/W4210257598"],"related_works":["https://openalex.org/W2904868555","https://openalex.org/W2020198693","https://openalex.org/W2952662149","https://openalex.org/W1926303568","https://openalex.org/W3155846532","https://openalex.org/W4386880480","https://openalex.org/W2361372973","https://openalex.org/W3124740722","https://openalex.org/W4389359147","https://openalex.org/W2065835655"],"abstract_inverted_index":{"Nowadays,":[0],"it":[1],"is":[2,40,60,150],"common":[3],"for":[4],"a":[5,131],"person":[6],"to":[7,19,43,81,105,114,123,126,135],"possess":[8],"different":[9,25],"identities":[10,22],"on":[11,56,90],"multiple":[12,144,153],"social":[13,155],"platforms.":[14],"Social":[15],"network":[16,29,84,112,132,140,156],"alignment":[17,30,74,141],"aims":[18,104],"match":[20],"the":[21,45,49,83,88,107,111,117,137,159,163,167],"that":[23,162],"from":[24],"networks.":[26],"Recently,":[27],"unsupervised":[28,51,73],"methods":[31,52],"have":[32],"received":[33],"significant":[34],"attention":[35],"since":[36],"no":[37],"identity":[38],"anchor":[39],"required.":[41],"However,":[42],"capture":[44],"relevance":[46],"between":[47],"identities,":[48],"existing":[50],"generally":[53],"rely":[54],"heavily":[55],"user":[57,91],"profiles,":[58],"which":[59],"unobtainable":[61],"and":[62,86,110,158],"unreliable":[63],"in":[64,121],"real-world":[65,154],"scenarios.":[66],"In":[67],"this":[68],"paper,":[69],"we":[70,129],"propose":[71,130],"an":[72],"framework":[75],"named":[76,98],"Large-Scale":[77],"Network":[78,100],"Alignment":[79],"(LSNA)":[80],"integrate":[82,106],"information":[85,109],"reduce":[87],"requirement":[89],"profile.":[92],"The":[93,147],"embedding":[94,118],"module":[95],"of":[96],"LSNA,":[97],"Cross":[99],"Embedding":[101],"Model":[102],"(CNEM),":[103],"topology":[108],"correlation":[113],"simultaneously":[115],"guide":[116],"process.":[119],"Moreover,":[120],"order":[122],"adapt":[124],"LSNA":[125],"large-scale":[127,139],"networks,":[128],"disassembling":[133],"strategy":[134],"divide":[136],"costly":[138],"problem":[142],"into":[143],"executable":[145],"sub-problems.":[146],"proposed":[148,164],"method":[149,165],"evaluated":[151],"over":[152],"datasets,":[157],"results":[160],"demonstrate":[161],"outperforms":[166],"state-of-the-art":[168],"methods.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
