{"id":"https://openalex.org/W4399794187","doi":"https://doi.org/10.1145/3637528.3671829","title":"Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling","display_name":"Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4399794187","doi":"https://doi.org/10.1145/3637528.3671829"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671829","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671829","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 SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2406.10425","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053042660","display_name":"Tianxiang Zhao","orcid":"https://orcid.org/0000-0003-4504-7809"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianxiang Zhao","raw_affiliation_strings":["The Pennsylvania State University, State College, USA"],"raw_orcid":"https://orcid.org/0000-0003-4504-7809","affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, State College, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102761357","display_name":"Dongsheng Luo","orcid":"https://orcid.org/0000-0003-4192-0826"},"institutions":[{"id":"https://openalex.org/I19700959","display_name":"Florida International University","ror":"https://ror.org/02gz6gg07","country_code":"US","type":"education","lineage":["https://openalex.org/I19700959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dongsheng Luo","raw_affiliation_strings":["Florida International University, Miami, USA"],"raw_orcid":"https://orcid.org/0000-0003-4192-0826","affiliations":[{"raw_affiliation_string":"Florida International University, Miami, USA","institution_ids":["https://openalex.org/I19700959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060725887","display_name":"X. D. Zhang","orcid":"https://orcid.org/0000-0003-0940-6595"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiang Zhang","raw_affiliation_strings":["The Pennsylvania State University, State College, USA"],"raw_orcid":"https://orcid.org/0000-0003-0940-6595","affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, State College, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011048500","display_name":"Suhang Wang","orcid":"https://orcid.org/0000-0003-3448-4878"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suhang Wang","raw_affiliation_strings":["The Pennsylvania State University, State College, USA"],"raw_orcid":"https://orcid.org/0000-0003-3448-4878","affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, State College, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7615,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.86377727,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4479","last_page":"4489"},"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":0.9993000030517578,"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":0.9993000030517578,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9577000141143799,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10028","display_name":"Topic Modeling","score":0.9509000182151794,"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":0.789065957069397},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5474140048027039},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5212774276733398},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4267062544822693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4164239466190338},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4064427316188812},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38932862877845764},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38495707511901855},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.19626042246818542}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.789065957069397},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5474140048027039},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5212774276733398},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4267062544822693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4164239466190338},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4064427316188812},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38932862877845764},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38495707511901855},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.19626042246818542}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3637528.3671829","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671829","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 SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2406.10425","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2406.10425","pdf_url":"https://arxiv.org/pdf/2406.10425","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2406.10425","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2406.10425","pdf_url":"https://arxiv.org/pdf/2406.10425","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G125128811","display_name":null,"funder_award_id":"W911NF-2110198","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G1432373144","display_name":null,"funder_award_id":"W911NF-21-1-","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G7366345995","display_name":"III: Small: Collaborative Research: Effective Labeled Data Generation via Generative Adversarial Learning","funder_award_id":"1909702","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7452299184","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306110","display_name":"U.S. Department of Homeland Security","ror":"https://ror.org/00jyr0d86"},{"id":"https://openalex.org/F4320307791","display_name":"Cisco Systems","ror":"https://ror.org/03yt1ez60"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399794187.pdf","grobid_xml":"https://content.openalex.org/works/W4399794187.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1966000522","https://openalex.org/W2052274922","https://openalex.org/W2104068492","https://openalex.org/W2148440006","https://openalex.org/W2155251704","https://openalex.org/W2593768305","https://openalex.org/W2617495708","https://openalex.org/W2735735104","https://openalex.org/W2959965583","https://openalex.org/W2963043696","https://openalex.org/W2964285681","https://openalex.org/W2981720610","https://openalex.org/W3009330671","https://openalex.org/W3012644407","https://openalex.org/W3039883906","https://openalex.org/W3093410149","https://openalex.org/W3169350676","https://openalex.org/W3169827396","https://openalex.org/W3182963544","https://openalex.org/W3207981989","https://openalex.org/W4210432355","https://openalex.org/W4224316953","https://openalex.org/W4292087343","https://openalex.org/W4293057355","https://openalex.org/W4387846296","https://openalex.org/W4394717706","https://openalex.org/W6680880821","https://openalex.org/W6784860860"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2345479200","https://openalex.org/W2183306018","https://openalex.org/W2849310602","https://openalex.org/W3006008237","https://openalex.org/W2419146053","https://openalex.org/W4388890789","https://openalex.org/W2088247287","https://openalex.org/W2963903416","https://openalex.org/W2932872266"],"abstract_inverted_index":{"In":[0,71],"this":[1,63,72],"paper,":[2],"we":[3,74,128,162],"tackle":[4],"a":[5,86,90,95,123,210],"new":[6],"problem":[7],"ofmulti-source":[8],"unsupervised":[9,28],"domain":[10,88,135,166],"adaptation":[11],"(MSUDA)":[12],"for":[13,31,81,99,133,160],"graphs,":[14],"where":[15],"models":[16],"trained":[17],"on":[18,215],"annotated":[19],"source":[20,50,109,134,154,169,199],"domains":[21],"need":[22],"to":[23,26,35,47,54,103,143,167,196],"be":[24],"transferred":[25],"the":[27,36,42,56,76,100,105,111,120,145,152,164,173,178,184,189,203,220,223],"target":[29,165],"graph":[30,59,217],"node":[32,92,138],"classification.":[33],"Due":[34],"discrepancy":[37],"in":[38,147,205],"distribution":[39],"across":[40,113],"domains,":[41],"key":[43],"challenge":[44],"is":[45,115,140],"how":[46,53],"select":[48,197],"good":[49],"instances":[51],"and":[52,94,117,127,182,201],"adapt":[55],"model.":[57],"Diverse":[58],"structures":[60],"further":[61,141],"complicate":[62],"problem,":[64],"rendering":[65],"previous":[66],"MSUDA":[67],"approaches":[68],"less":[69],"effective.":[70],"work,":[73],"present":[75],"framework":[77],"Selective":[78],"Multi-source":[79],"Adaptation":[80],"Graph":[82],"(SelMAG":[83],"),":[84],"with":[85,119,209],"graph-modeling-based":[87],"selector,":[89,93],"sub-graph":[91],"bi-level":[96],"alignment":[97,204],"objective":[98],"adaptation.":[101],"Concretely,":[102],"facilitate":[104],"identification":[106],"of":[107,122,149,222],"informative":[108,198],"data,":[110],"similarity":[112],"graphs":[114],"disentangled":[116],"measured":[118],"transferability":[121,148],"graph-modeling":[124],"task":[125],"set,":[126],"use":[129],"it":[130],"as":[131],"evidence":[132],"selection.":[136],"A":[137],"selector":[139],"incorporated":[142],"capture":[144],"variation":[146],"nodes":[150],"within":[151],"same":[153],"domain.":[155],"To":[156],"learn":[157],"invariant":[158],"features":[159],"adaptation,":[161],"align":[163],"selected":[168],"data":[170,200],"both":[171],"at":[172,183],"embedding":[174],"space":[175],"by":[176,187],"minimizing":[177],"optimal":[179],"transport":[180],"distance":[181],"classification":[185],"level":[186],"distilling":[188],"label":[190],"function.":[191],"Modules":[192],"are":[193],"explicitly":[194],"learned":[195],"conduct":[202],"virtual":[206],"training":[207],"splits":[208],"meta-learning":[211],"strategy.":[212],"Experimental":[213],"results":[214],"five":[216],"datasets":[218],"show":[219],"effectiveness":[221],"proposed":[224],"method.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2024-06-19T00:00:00"}