{"id":"https://openalex.org/W4282010430","doi":"https://doi.org/10.1145/3514221.3517870","title":"Domain Adaptation for Deep Entity Resolution","display_name":"Domain Adaptation for Deep Entity Resolution","publication_year":2022,"publication_date":"2022-06-10","ids":{"openalex":"https://openalex.org/W4282010430","doi":"https://doi.org/10.1145/3514221.3517870"},"language":"en","primary_location":{"id":"doi:10.1145/3514221.3517870","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3514221.3517870","pdf_url":null,"source":{"id":"https://openalex.org/S4363608845","display_name":"Proceedings of the 2022 International Conference on Management of Data","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 International Conference on Management of 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/A5082583725","display_name":"Jianhong Tu","orcid":"https://orcid.org/0009-0001-1554-1614"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianhong Tu","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100739546","display_name":"Ju Fan","orcid":"https://orcid.org/0000-0003-4729-9903"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ju Fan","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101824160","display_name":"Nan Tang","orcid":"https://orcid.org/0000-0003-2832-0295"},"institutions":[{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Nan Tang","raw_affiliation_strings":["Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar"],"affiliations":[{"raw_affiliation_string":"Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100396049","display_name":"Peng Wang","orcid":"https://orcid.org/0000-0002-5931-8852"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Wang","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101797040","display_name":"Chengliang Chai","orcid":"https://orcid.org/0000-0001-8080-5594"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengliang Chai","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100451576","display_name":"Guoliang Li","orcid":"https://orcid.org/0000-0002-1398-0621"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoliang Li","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075199300","display_name":"Ruixue Fan","orcid":"https://orcid.org/0000-0002-9826-7349"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruixue Fan","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008721449","display_name":"Xiaoyong Du","orcid":"https://orcid.org/0000-0002-5757-9135"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyong Du","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5082583725"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":9.7815,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.98982325,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"443","last_page":"457"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9764000177383423,"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/T10028","display_name":"Topic Modeling","score":0.9641000032424927,"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":0.8360562324523926},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6922379732131958},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6794657707214355},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6705566644668579},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6703925132751465},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.665625810623169},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6149216294288635},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5381228923797607},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4837351143360138},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.48315852880477905},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4645046889781952},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.4509446620941162},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.35517141222953796},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.333942174911499}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8360562324523926},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6922379732131958},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6794657707214355},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6705566644668579},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6703925132751465},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.665625810623169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6149216294288635},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5381228923797607},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4837351143360138},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.48315852880477905},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4645046889781952},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.4509446620941162},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35517141222953796},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.333942174911499},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3514221.3517870","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3514221.3517870","pdf_url":null,"source":{"id":"https://openalex.org/S4363608845","display_name":"Proceedings of the 2022 International Conference on Management of Data","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 International Conference on Management of Data","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5299999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1964786778","https://openalex.org/W2008635359","https://openalex.org/W2012668444","https://openalex.org/W2035615211","https://openalex.org/W2111625757","https://openalex.org/W2123561513","https://openalex.org/W2145094598","https://openalex.org/W2159570078","https://openalex.org/W2164456230","https://openalex.org/W2171472464","https://openalex.org/W2212660284","https://openalex.org/W2428834396","https://openalex.org/W2478454054","https://openalex.org/W2593768305","https://openalex.org/W2604474127","https://openalex.org/W2612177096","https://openalex.org/W2612619809","https://openalex.org/W2775696413","https://openalex.org/W2786808285","https://openalex.org/W2798649495","https://openalex.org/W2799012717","https://openalex.org/W2808345493","https://openalex.org/W2889357608","https://openalex.org/W2898956098","https://openalex.org/W2945883855","https://openalex.org/W2962899390","https://openalex.org/W2963275094","https://openalex.org/W2963767194","https://openalex.org/W2964109570","https://openalex.org/W2964189376","https://openalex.org/W2964288524","https://openalex.org/W2979826702","https://openalex.org/W2997574889","https://openalex.org/W2998172865","https://openalex.org/W2998666297","https://openalex.org/W3011807731","https://openalex.org/W3022187094","https://openalex.org/W3030662011","https://openalex.org/W3039883906","https://openalex.org/W3041133507","https://openalex.org/W3045211065","https://openalex.org/W3096174636","https://openalex.org/W3138971549","https://openalex.org/W3147796863","https://openalex.org/W3161956575","https://openalex.org/W3197468999"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W2086519370","https://openalex.org/W2028665553","https://openalex.org/W2087343574","https://openalex.org/W2535915176","https://openalex.org/W2105860728","https://openalex.org/W2535808783"],"abstract_inverted_index":{"Entity":[0,153],"resolution":[1],"(ER)":[2],"is":[3,98,117,125],"a":[4,26,37,55,73,81,86,94,134,147,165],"core":[5],"problem":[6,38],"of":[7,28,133,137,167,174,201],"data":[8],"integration.":[9],"The":[10],"state-of-the-art":[11],"(SOTA)":[12],"results":[13],"on":[14,214],"ER":[15,48,76,83,159],"are":[16],"achieved":[17,106],"by":[18],"deep":[19],"learning":[20],"(DL)":[21],"based":[22,213],"methods,":[23],"trained":[24],"with":[25,54,93],"lot":[27],"labeled":[29,61],"matching/non-matching":[30],"entity":[31],"pairs.":[32],"This":[33,97],"may":[34],"not":[35,118],"be":[36],"when":[39],"using":[40],"well-prepared":[41],"benchmark":[42],"datasets.":[43,62],"Nevertheless,":[44],"for":[45,85,121,140,151,170,203,208],"many":[46],"real-world":[47],"applications,":[49],"the":[50,129,171,187,194],"situation":[51],"changes":[52],"dramatically,":[53],"painful":[56],"issue":[57],"to":[58,68,126,192],"collect":[59],"large-scale":[60],"In":[63],"this":[64,143],"paper,":[65],"we":[66,71,79,145],"seek":[67],"answer:":[69],"If":[70],"have":[72],"well-labeled":[74],"source":[75],"dataset,":[77,88],"can":[78],"train":[80],"DL-based":[82],"model":[84],"target":[87],"without":[89],"any":[90],"labels":[91],"or":[92],"few":[95],"labels?":[96],"known":[99],"as":[100],"domain":[101],"adaptation":[102],"(DA),":[103],"which":[104],"has":[105],"great":[107],"successes":[108],"in":[109,160],"computer":[110],"vision":[111],"and":[112,131,180,197],"natural":[113],"language":[114],"processing,":[115],"but":[116],"systematically":[119,127],"studied":[120],"ER.":[122,141,204],"Our":[123],"goal":[124],"explore":[128,193],"benefits":[130],"limitations":[132],"wide":[135],"range":[136],"DA":[138,202],"methods":[139],"To":[142],"purpose,":[144],"develop":[146],"DADER":[148],"(Domain":[149],"Adaptation":[150],"Deep":[152],"Resolution)":[154],"framework":[155],"that":[156],"significantly":[157],"advances":[158],"applying":[161],"DA.":[162],"We":[163,183,205],"define":[164],"space":[166,196],"design":[168,195,211],"solutions":[169,212],"three":[172],"modules":[173],"DADER,":[175],"namely":[176],"Feature":[177,181],"Extractor,":[178],"Matcher,":[179],"Aligner.":[182],"conduct":[184],"so":[185],"far":[186],"most":[188],"comprehensive":[189],"experimental":[190],"study":[191],"compare":[198],"different":[199],"choices":[200],"provide":[206],"guidance":[207],"selecting":[209],"appropriate":[210],"extensive":[215],"experiments.":[216]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
