{"id":"https://openalex.org/W3096209122","doi":"https://doi.org/10.1109/tbdata.2020.3034201","title":"Domain Adaptive Network Embedding","display_name":"Domain Adaptive Network Embedding","publication_year":2020,"publication_date":"2020-10-27","ids":{"openalex":"https://openalex.org/W3096209122","doi":"https://doi.org/10.1109/tbdata.2020.3034201","mag":"3096209122"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2020.3034201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2020.3034201","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-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/A5088976879","display_name":"Guojie Song","orcid":"https://orcid.org/0000-0001-8295-2520"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guojie Song","raw_affiliation_strings":["Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8295-2520","affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017932163","display_name":"Yizhou Zhang","orcid":"https://orcid.org/0000-0003-0450-2406"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I144571360","display_name":"Viterbo University","ror":"https://ror.org/039p8pn96","country_code":"US","type":"education","lineage":["https://openalex.org/I144571360"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yizhou Zhang","raw_affiliation_strings":["Department of Computer Science of Viterbi School of Engineering, University of Southern California, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science of Viterbi School of Engineering, University of Southern California, CA, USA","institution_ids":["https://openalex.org/I1174212","https://openalex.org/I144571360"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027301562","display_name":"Lingjun Xu","orcid":"https://orcid.org/0000-0003-0417-8351"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingjun Xu","raw_affiliation_strings":["School of Electronic Engineering and Computer Science, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0417-8351","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering and Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060287641","display_name":"Haibing Lu","orcid":"https://orcid.org/0000-0003-0266-6191"},"institutions":[{"id":"https://openalex.org/I16269868","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447","country_code":"US","type":"education","lineage":["https://openalex.org/I16269868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haibing Lu","raw_affiliation_strings":["department of Information System and Analytics, Santa Clara University, CA, USA"],"raw_orcid":"https://orcid.org/0000-0003-0266-6191","affiliations":[{"raw_affiliation_string":"department of Information System and Analytics, Santa Clara University, CA, USA","institution_ids":["https://openalex.org/I16269868"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8043,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.79737827,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":"8","issue":"5","first_page":"1220","last_page":"1232"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9973000288009644,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9973000288009644,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9961000084877014,"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/T12676","display_name":"Machine Learning and ELM","score":0.9559999704360962,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8119332790374756},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7811192274093628},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.49072253704071045},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46424731612205505},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4468100965023041},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4241732358932495},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.11572617292404175}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8119332790374756},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7811192274093628},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.49072253704071045},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46424731612205505},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4468100965023041},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4241732358932495},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.11572617292404175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2020.3034201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2020.3034201","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3456178228","display_name":"\u9762\u5411\u793e\u4f1a\u7f51\u7edc\u4fe1\u606f\u4f20\u64ad\u7684\u7f51\u7edc\u91cd\u6784\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61572041","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7851798376","display_name":null,"funder_award_id":"61876006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W82211948","https://openalex.org/W1888005072","https://openalex.org/W2057685268","https://openalex.org/W2116873850","https://openalex.org/W2154851992","https://openalex.org/W2159291411","https://openalex.org/W2337399039","https://openalex.org/W2593414223","https://openalex.org/W2593768305","https://openalex.org/W2792234394","https://openalex.org/W2808087697","https://openalex.org/W2895187988","https://openalex.org/W2896831016","https://openalex.org/W2907935785","https://openalex.org/W2912240430","https://openalex.org/W2912719334","https://openalex.org/W2949435814","https://openalex.org/W2951527381","https://openalex.org/W2962756421","https://openalex.org/W2963261224","https://openalex.org/W2963672650","https://openalex.org/W2963917673","https://openalex.org/W2969212296","https://openalex.org/W2981405661","https://openalex.org/W3100078588","https://openalex.org/W3102794461","https://openalex.org/W3103659988","https://openalex.org/W3104097132","https://openalex.org/W6636267554","https://openalex.org/W6639480849","https://openalex.org/W6640963894","https://openalex.org/W6683633756","https://openalex.org/W6699364125","https://openalex.org/W6726873649","https://openalex.org/W6733322467","https://openalex.org/W6734490199","https://openalex.org/W6738964360","https://openalex.org/W6741832134","https://openalex.org/W6747469349","https://openalex.org/W6754929296","https://openalex.org/W6776488958"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Recent":[0],"works":[1],"reveal":[2],"that":[3,51,154],"network":[4,48,145,161],"embedding":[5,28,49,98,103,146,162],"techniques":[6],"enable":[7],"many":[8],"machine":[9],"learning":[10,27,143],"models":[11],"to":[12,45,79,91],"handle":[13],"diverse":[14],"downstream":[15,53],"tasks":[16],"on":[17,26,38,56,104],"graph-structured":[18],"data.":[19],"However,":[20],"as":[21,60],"previous":[22],"methods":[23],"usually":[24],"focus":[25],"for":[29],"a":[30,47,68,94,126],"single":[31],"network,":[32],"they":[33],"cannot":[34],"learn":[35,80],"representations":[36],"transferable":[37,81,144],"multiple":[39,87],"networks.":[40],"Hence,":[41],"it":[42],"is":[43],"important":[44],"design":[46],"algorithm":[50],"supports":[52],"model":[54],"transferring":[55],"different":[57,105],"networks,":[58],"known":[59],"domain":[61,166],"adaptation.":[62],"In":[63,83],"this":[64],"article,":[65],"we":[66],"propose":[67],"Domain":[69],"Adaptive":[70],"Network":[71,78],"Embedding":[72],"framework,":[73],"which":[74],"applies":[75],"Graph":[76],"Convolutional":[77],"embedding.":[82],"DANE,":[84],"nodes":[85],"from":[86],"networks":[88,106],"are":[89,107,122],"encoded":[90],"vectors":[92],"via":[93],"shared":[95],"and":[96,134,169],"aligned":[97,109],"space.":[99],"The":[100],"distribution":[101],"of":[102,130],"further":[108],"by":[110],"Adversarial":[111],"Learning":[112],"Regularization.":[113],"To":[114],"achieve":[115],"better":[116],"performance":[117,175],"in":[118,142,164],"scenarios":[119],"where":[120],"labels":[121],"provided,":[123],"DANE":[124],"adopts":[125],"cross-entropy":[127],"error":[128],"term":[129],"the":[131,155,170,174],"GCN":[132],"framework":[133,157],"class":[135],"centroid":[136],"aligning":[137],"method.":[138],"Moreover,":[139],"DANE's":[140],"advantages":[141],"can":[147],"be":[148],"guaranteed":[149],"theoretically.":[150],"Extensive":[151],"experiments":[152],"reflect":[153],"proposed":[156],"outperforms":[158],"other":[159],"well-recognized":[160],"baselines":[163],"cross-network":[165],"adaptation":[167],"tasks,":[168],"semi-supervised":[171],"components":[172],"improve":[173],"significantly.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}