{"id":"https://openalex.org/W4391054937","doi":"https://doi.org/10.14778/3632093.3632096","title":"Blocker and Matcher Can Mutually Benefit: A Co-Learning Framework for Low-Resource Entity Resolution","display_name":"Blocker and Matcher Can Mutually Benefit: A Co-Learning Framework for Low-Resource Entity Resolution","publication_year":2023,"publication_date":"2023-11-01","ids":{"openalex":"https://openalex.org/W4391054937","doi":"https://doi.org/10.14778/3632093.3632096"},"language":"en","primary_location":{"id":"doi:10.14778/3632093.3632096","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3632093.3632096","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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":"Proceedings of the VLDB Endowment","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/A5021674757","display_name":"Shiwen Wu","orcid":"https://orcid.org/0000-0003-1072-7222"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Shiwen Wu","raw_affiliation_strings":["The Hong Kong University of Science and Technology"],"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024471982","display_name":"Qiyu Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Qiyu Wu","raw_affiliation_strings":["The University of Tokyo"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022753479","display_name":"Honghua Dong","orcid":"https://orcid.org/0009-0006-8298-4059"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]},{"id":"https://openalex.org/I4210127509","display_name":"Vector Institute","ror":"https://ror.org/03kqdja62","country_code":"CA","type":"facility","lineage":["https://openalex.org/I4210127509"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Honghua Dong","raw_affiliation_strings":["University of Toronto & Vector Institute"],"affiliations":[{"raw_affiliation_string":"University of Toronto & Vector Institute","institution_ids":["https://openalex.org/I4210127509","https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004652254","display_name":"Wen Hua","orcid":"https://orcid.org/0000-0001-5456-7035"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wen Hua","raw_affiliation_strings":["The Hong Kong Polytechnic University"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011384237","display_name":"Xiaofang Zhou","orcid":"https://orcid.org/0000-0001-6343-1455"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaofang Zhou","raw_affiliation_strings":["The Hong Kong University of Science and Technology"],"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology","institution_ids":["https://openalex.org/I200769079"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5021674757"],"corresponding_institution_ids":["https://openalex.org/I200769079"],"apc_list":null,"apc_paid":null,"fwci":1.5563,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.84949633,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"17","issue":"3","first_page":"292","last_page":"304"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9998000264167786,"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":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9900000095367432,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9623000025749207,"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/benchmark","display_name":"Benchmark (surveying)","score":0.8259569406509399},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7705023884773254},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.5632796287536621},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5389102101325989},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5247281193733215},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48465973138809204},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47251754999160767},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.4242880642414093},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3260008692741394}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8259569406509399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7705023884773254},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.5632796287536621},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5389102101325989},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5247281193733215},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48465973138809204},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47251754999160767},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.4242880642414093},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3260008692741394},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.14778/3632093.3632096","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3632093.3632096","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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":"Proceedings of the VLDB Endowment","raw_type":"journal-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-135547","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-135547","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"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":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2048679005","https://openalex.org/W2399361902","https://openalex.org/W2546672044","https://openalex.org/W2781528640","https://openalex.org/W2798649495","https://openalex.org/W2913251325","https://openalex.org/W2946504770","https://openalex.org/W2951147191","https://openalex.org/W2962804657","https://openalex.org/W2963284996","https://openalex.org/W2963469388","https://openalex.org/W2970641574","https://openalex.org/W2971681342","https://openalex.org/W2979826702","https://openalex.org/W2992897306","https://openalex.org/W3012733951","https://openalex.org/W3014295153","https://openalex.org/W3014705052","https://openalex.org/W3099734810","https://openalex.org/W3103177583","https://openalex.org/W3123375411","https://openalex.org/W3156636935","https://openalex.org/W3174036215","https://openalex.org/W3174836606","https://openalex.org/W3197468999","https://openalex.org/W4205196528","https://openalex.org/W4205807230","https://openalex.org/W4246012463","https://openalex.org/W4281721601","https://openalex.org/W4282010430","https://openalex.org/W4309131876","https://openalex.org/W4380433186","https://openalex.org/W4381610063"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W4230315250","https://openalex.org/W2086519370","https://openalex.org/W2087343574"],"abstract_inverted_index":{"Entity":[0],"resolution":[1],"(ER)":[2],"approaches":[3],"typically":[4],"consist":[5],"of":[6,63,145,181],"a":[7,10,60,79],"blocker":[8,23,106,120,195],"and":[9,17,29,107,121,161,196],"matcher.":[11,198],"They":[12],"share":[13,124],"the":[14,22,30,35,40,45,105,108,119,122,138,143,194,197],"same":[15,41],"goal":[16],"cooperate":[18],"in":[19,53,147],"different":[20],"roles:":[21],"first":[24],"quickly":[25],"removes":[26],"obvious":[27],"non-matches,":[28],"matcher":[31,109,123],"subsequently":[32],"determines":[33],"whether":[34],"remaining":[36],"pairs":[37],"refer":[38],"to":[39,74,81],"real-world":[42],"entity.":[43],"Despite":[44],"state-of-the-art":[46],"performance":[47],"achieved":[48],"by":[49,110,178],"deep":[50],"learning":[51],"methods":[52],"ER,":[54,100],"these":[55],"techniques":[56,153],"often":[57],"rely":[58],"on":[59,167],"large":[61],"amount":[62],"labeled":[64],"data":[65],"for":[66,99],"training,":[67],"which":[68,136],"can":[69],"be":[70],"challenging":[71],"or":[72],"costly":[73],"obtain.":[75],"Thus,":[76],"there":[77],"is":[78],"need":[80],"develop":[82,151],"effective":[83],"ER":[84],"systems":[85],"under":[86],"low-resource":[87],"settings.":[88],"In":[89,115],"this":[90],"work,":[91],"we":[92,117,150,170],"propose":[93],"an":[94,179],"end-to-end":[95],"iterative":[96],"Co-learning":[97],"framework":[98,175,189],"aimed":[101],"at":[102],"jointly":[103],"training":[104],"leveraging":[111],"their":[112,125],"cooperative":[113],"relationship.":[114],"particular,":[116],"let":[118],"learned":[126],"knowledge":[127],"with":[128],"each":[129],"other":[130],"via":[131],"iteratively":[132],"updated":[133],"pseudo":[134,148],"labels,":[135,149],"broaden":[137],"supervision":[139],"signals.":[140],"To":[141],"mitigate":[142],"impact":[144],"noise":[146],"optimization":[152],"from":[154],"three":[155],"aspects:":[156],"label":[157,159],"generation,":[158],"selection":[160],"model":[162],"training.":[163],"Through":[164],"extensive":[165],"experiments":[166],"benchmark":[168],"datasets,":[169],"demonstrate":[171],"that":[172,187],"our":[173,184,188],"proposed":[174],"outperforms":[176],"baselines":[177],"average":[180],"9.13--51.55%.":[182],"Furthermore,":[183],"analysis":[185],"confirms":[186],"achieves":[190],"mutual":[191],"benefits":[192],"between":[193]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-04T09:10:02.777135","created_date":"2025-10-10T00:00:00"}