{"id":"https://openalex.org/W4205661033","doi":"https://doi.org/10.1145/3492804","title":"Multiple Graphs and Low-Rank Embedding for Multi-Source Heterogeneous Domain Adaptation","display_name":"Multiple Graphs and Low-Rank Embedding for Multi-Source Heterogeneous Domain Adaptation","publication_year":2022,"publication_date":"2022-01-08","ids":{"openalex":"https://openalex.org/W4205661033","doi":"https://doi.org/10.1145/3492804"},"language":"en","primary_location":{"id":"doi:10.1145/3492804","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3492804","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from 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/A5089907983","display_name":"Hanrui Wu","orcid":"https://orcid.org/0000-0003-3565-6635"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanrui Wu","raw_affiliation_strings":["Department of Computer Science, Jinan University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-3565-6635","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010561682","display_name":"Michael K. Ng","orcid":"https://orcid.org/0000-0001-6833-5227"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Michael K. Ng","raw_affiliation_strings":["Department of Mathematics, The University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0001-6833-5227","affiliations":[{"raw_affiliation_string":"Department of Mathematics, The University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.837,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.86988501,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"16","issue":"4","first_page":"1","last_page":"25"},"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":0.9997000098228455,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9541000127792358,"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/T12676","display_name":"Machine Learning and ELM","score":0.949400007724762,"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/embedding","display_name":"Embedding","score":0.7924336194992065},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7119917273521423},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6745091676712036},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6743026971817017},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6522184610366821},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6316561698913574},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.4466205835342407},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4437602460384369},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44240713119506836},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4306703805923462},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4257512092590332},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4166320562362671},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3669620752334595},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2001550793647766},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.16202440857887268}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7924336194992065},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7119917273521423},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6745091676712036},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6743026971817017},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6522184610366821},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6316561698913574},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.4466205835342407},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4437602460384369},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44240713119506836},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4306703805923462},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4257512092590332},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4166320562362671},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3669620752334595},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2001550793647766},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.16202440857887268},{"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/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3492804","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3492804","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1985697265","https://openalex.org/W1988348003","https://openalex.org/W1988790447","https://openalex.org/W1998894210","https://openalex.org/W2005650084","https://openalex.org/W2050398567","https://openalex.org/W2067624665","https://openalex.org/W2109553965","https://openalex.org/W2115403315","https://openalex.org/W2119821739","https://openalex.org/W2153635508","https://openalex.org/W2165698076","https://openalex.org/W2170607218","https://openalex.org/W2326887180","https://openalex.org/W2422697180","https://openalex.org/W2519936666","https://openalex.org/W2520858298","https://openalex.org/W2552639984","https://openalex.org/W2593713917","https://openalex.org/W2602480929","https://openalex.org/W2614580201","https://openalex.org/W2735735104","https://openalex.org/W2736590139","https://openalex.org/W2772118439","https://openalex.org/W2904255843","https://openalex.org/W2943293047","https://openalex.org/W2946170651","https://openalex.org/W2946948585","https://openalex.org/W2947733970","https://openalex.org/W2955547856","https://openalex.org/W2964281014","https://openalex.org/W2981401872","https://openalex.org/W2981720610","https://openalex.org/W2984221099","https://openalex.org/W2999309192","https://openalex.org/W3033245467","https://openalex.org/W3046682702","https://openalex.org/W3047770672","https://openalex.org/W3047993974","https://openalex.org/W3080610273","https://openalex.org/W3100880133","https://openalex.org/W3131163951","https://openalex.org/W3132625589","https://openalex.org/W3171602993","https://openalex.org/W3182116573","https://openalex.org/W4200257514"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W3111219495","https://openalex.org/W3095487414","https://openalex.org/W4288048773","https://openalex.org/W2901026139","https://openalex.org/W3011471740","https://openalex.org/W2772359885","https://openalex.org/W2213679718","https://openalex.org/W2884580467","https://openalex.org/W2572315477"],"abstract_inverted_index":{"Multi-source":[0,25],"domain":[1,16,107,110],"adaptation":[2],"is":[3,31,153],"a":[4,58],"challenging":[5],"topic":[6],"in":[7,161],"transfer":[8],"learning,":[9],"especially":[10],"when":[11],"the":[12,37,47,52,70,82,86,92,96,103,113,130,135,138,149,158,177,180],"data":[13],"of":[14,22,36,74,85,105,137,151,157,163,179],"each":[15],"are":[17],"represented":[18],"by":[19],"different":[20],"kinds":[21],"features,":[23],"i.e.,":[24],"Heterogeneous":[26],"Domain":[27],"Adaptation":[28],"(MHDA).":[29],"It":[30],"important":[32],"to":[33,128],"take":[34],"advantage":[35],"knowledge":[38],"extracted":[39],"from":[40],"multiple":[41,75,78,114],"sources":[42],"as":[43,45,167],"well":[44],"bridge":[46],"heterogeneous":[48],"spaces":[49],"for":[50],"handling":[51],"MHDA":[53],"paradigm.":[54],"This":[55],"article":[56],"proposes":[57],"novel":[59],"method":[60,140],"named":[61],"Multiple":[62],"Graphs":[63],"and":[64,80,109,116,174],"Low-rank":[65],"Embedding":[66],"(MGLE),":[67],"which":[68],"models":[69],"local":[71],"structure":[72],"information":[73],"domains":[76],"using":[77],"graphs":[79,115],"learns":[81],"low-rank":[83,117],"embedding":[84,94,118],"target":[87,98],"domain.":[88],"Then,":[89],"MGLE":[90,152],"augments":[91],"learned":[93],"with":[95],"original":[97],"data.":[99],"Specifically,":[100],"we":[101,122],"introduce":[102],"modules":[104],"both":[106],"discrepancy":[108],"relevance":[111],"into":[112],"learning":[119],"procedure.":[120],"Subsequently,":[121],"develop":[123],"an":[124],"iterative":[125],"optimization":[126],"algorithm":[127],"solve":[129],"resulting":[131],"problem.":[132],"We":[133],"evaluate":[134],"effectiveness":[136,178],"proposed":[139,181],"on":[141],"several":[142,164],"real-world":[143],"datasets.":[144],"Promising":[145],"results":[146],"show":[147],"that":[148,156],"performance":[150],"better":[154],"than":[155],"baseline":[159],"methods":[160],"terms":[162],"metrics,":[165],"such":[166],"AUC,":[168],"MAE,":[169],"accuracy,":[170],"precision,":[171],"F1":[172],"score,":[173],"MCC,":[175],"demonstrating":[176],"method.":[182]},"counts_by_year":[{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}