{"id":"https://openalex.org/W3007652077","doi":"https://doi.org/10.1109/bigdata47090.2019.9006430","title":"DNA: Dynamic Social Network Alignment","display_name":"DNA: Dynamic Social Network Alignment","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3007652077","doi":"https://doi.org/10.1109/bigdata47090.2019.9006430","mag":"3007652077"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9006430","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006430","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/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":true,"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/A5014850601","display_name":"Jian Wen","orcid":null},"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":"Jian Wen","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/A5100318687"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":2.1676,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.90928388,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1224","last_page":"1231"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9993000030517578,"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":0.9553999900817871,"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":0.7904253005981445},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5791038274765015},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5725694298744202},{"id":"https://openalex.org/keywords/dynamic-network-analysis","display_name":"Dynamic network analysis","score":0.536813497543335},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.5198484063148499},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5124219059944153},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5050693154335022},{"id":"https://openalex.org/keywords/social-network-analysis","display_name":"Social network analysis","score":0.4927678406238556},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.44796305894851685},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44284215569496155},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.4288710057735443},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4053443670272827},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39052465558052063},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.17708826065063477},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10314390063285828},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.08785372972488403}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7904253005981445},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5791038274765015},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5725694298744202},{"id":"https://openalex.org/C13540734","wikidata":"https://www.wikidata.org/wiki/Q5318996","display_name":"Dynamic network analysis","level":2,"score":0.536813497543335},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.5198484063148499},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5124219059944153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5050693154335022},{"id":"https://openalex.org/C114713312","wikidata":"https://www.wikidata.org/wiki/Q7551269","display_name":"Social network analysis","level":3,"score":0.4927678406238556},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.44796305894851685},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44284215569496155},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.4288710057735443},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4053443670272827},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39052465558052063},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.17708826065063477},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10314390063285828},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.08785372972488403},{"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9006430","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006430","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":0.7799999713897705,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W812851569","https://openalex.org/W1496564895","https://openalex.org/W1888005072","https://openalex.org/W1980680715","https://openalex.org/W2047532797","https://openalex.org/W2055345291","https://openalex.org/W2058036501","https://openalex.org/W2060960003","https://openalex.org/W2102113734","https://openalex.org/W2133299088","https://openalex.org/W2154851992","https://openalex.org/W2168474259","https://openalex.org/W2242161203","https://openalex.org/W2247394048","https://openalex.org/W2374981910","https://openalex.org/W2391555403","https://openalex.org/W2393319904","https://openalex.org/W2514012150","https://openalex.org/W2571692900","https://openalex.org/W2572926828","https://openalex.org/W2583803680","https://openalex.org/W2584993989","https://openalex.org/W2598689838","https://openalex.org/W2787927827","https://openalex.org/W2788259657","https://openalex.org/W2793022729","https://openalex.org/W2800544704","https://openalex.org/W2808087697","https://openalex.org/W2808254354","https://openalex.org/W2808409763","https://openalex.org/W2808771744","https://openalex.org/W2808867307","https://openalex.org/W2808908091","https://openalex.org/W2809280072","https://openalex.org/W2896831016","https://openalex.org/W2896997271","https://openalex.org/W2904205492","https://openalex.org/W2911702602","https://openalex.org/W2912505106","https://openalex.org/W2914821591","https://openalex.org/W2919997401","https://openalex.org/W2962756421","https://openalex.org/W2962975498","https://openalex.org/W2963512530","https://openalex.org/W2963885834","https://openalex.org/W2964015378","https://openalex.org/W2964142522","https://openalex.org/W3104097132","https://openalex.org/W6622955728","https://openalex.org/W6662241857","https://openalex.org/W6675365184","https://openalex.org/W6679726148","https://openalex.org/W6690230747","https://openalex.org/W6726220244","https://openalex.org/W6726873649","https://openalex.org/W6731581786","https://openalex.org/W6731785350","https://openalex.org/W6746459935","https://openalex.org/W6747581376","https://openalex.org/W6748348311","https://openalex.org/W6749122568","https://openalex.org/W6750999514"],"related_works":["https://openalex.org/W3021077433","https://openalex.org/W2952662149","https://openalex.org/W2793616590","https://openalex.org/W2183090405","https://openalex.org/W3200975495","https://openalex.org/W4288391523","https://openalex.org/W2075666982","https://openalex.org/W3160699245","https://openalex.org/W2782955270","https://openalex.org/W2065835655"],"abstract_inverted_index":{"Social":[0],"network":[1,26,56],"alignment,":[2,167],"aligning":[3,70],"different":[4],"social":[5,25,40,55,72,82,183],"networks":[6,41],"on":[7,224],"their":[8],"common":[9,199],"users,":[10],"is":[11],"receiving":[12],"dramatic":[13],"attention":[14],"from":[15,176],"both":[16,109],"academic":[17],"and":[18,30,111,131,156,227],"industry.":[19],"All":[20],"existing":[21],"studies":[22],"consider":[23],"the":[24,37,43,61,67,97,116,121,125,132,136,150,165,170,177,230,236],"to":[27,53,65,95,100,148,196],"be":[28,51],"static":[29],"neglect":[31],"its":[32],"inherent":[33],"dynamics.":[34],"In":[35],"fact,":[36],"dynamics":[38,99,123,155],"of":[39,46,69,124,135,173,201],"contain":[42],"discriminative":[44],"pattern":[45,127],"an":[47,174,212],"individual,":[48],"which":[49],"can":[50],"leveraged":[52],"facilitate":[54],"alignment.":[57,102],"Hence,":[58],"we":[59,77,119,168,210],"for":[60,159],"first":[62],"time":[63],"propose":[64,78],"study":[66],"problem":[68],"dynamic":[71,182],"networks.":[73],"Towards":[74],"this":[75,207],"end,":[76],"a":[79,87,143,187,198],"novel":[80,144],"Dynamic":[81],"Network":[83],"Alignment":[84],"(DNA)":[85],"framework,":[86],"unified":[88,188],"optimization":[89,189,208],"approach":[90,190],"over":[91],"deep":[92,145,193],"neural":[93,146,194],"architectures,":[94],"unfold":[96],"fruitful":[98],"perform":[101],"However,":[103],"it":[104],"faces":[105],"tremendous":[106],"challenges":[107],"in":[108,128,180],"modeling":[110],"optimization:":[112],"(1)":[113],"To":[114,163,205],"model":[115,164],"intra-network":[117],"dynamics,":[118],"explore":[120],"local":[122,154],"latent":[126],"friending":[129],"evolvement":[130],"global":[133,157],"consistency":[134,158],"representation":[137],"similarity":[138],"with":[139,216],"neighbors.":[140],"We":[141,185,220],"design":[142,186,211],"architecture":[147],"obtain":[149],"dual":[151,178],"embedding":[152,179],"capturing":[153],"each":[160,181],"user.":[161],"(2)":[162],"inter-network":[166],"exploit":[169],"underlying":[171],"identity":[172,202],"individual":[175],"network.":[184],"interplaying":[191],"proposed":[192,231],"architectures":[195],"construct":[197],"subspace":[200],"embeddings.":[203],"(3)":[204],"address":[206],"problem,":[209],"effective":[213],"alternating":[214],"algorithm":[215],"solid":[217],"theoretical":[218],"guarantees.":[219],"conduct":[221],"extensive":[222],"experiments":[223],"real-world":[225],"datasets":[226],"show":[228],"that":[229],"DNA":[232],"framework":[233],"substantially":[234],"outperforms":[235],"state-of-the-art":[237],"methods.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":4}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
