{"id":"https://openalex.org/W4385341770","doi":"https://doi.org/10.1007/s10489-023-04516-5","title":"Active pairwise distance learning for efficient labeling of large datasets by human experts","display_name":"Active pairwise distance learning for efficient labeling of large datasets by human experts","publication_year":2023,"publication_date":"2023-07-28","ids":{"openalex":"https://openalex.org/W4385341770","doi":"https://doi.org/10.1007/s10489-023-04516-5"},"language":"en","primary_location":{"id":"doi:10.1007/s10489-023-04516-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-023-04516-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-04516-5.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-04516-5.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001885546","display_name":"Joris Pries","orcid":"https://orcid.org/0000-0002-4429-6531"},"institutions":[{"id":"https://openalex.org/I1341640284","display_name":"Centrum Wiskunde & Informatica","ror":"https://ror.org/00x7ekv49","country_code":"NL","type":"facility","lineage":["https://openalex.org/I1341640284","https://openalex.org/I2800991832","https://openalex.org/I4405262988"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Joris Pries","raw_affiliation_strings":["Department of Stochastics, Centrum Wiskunde & Informatica, Science Park 123, Amsterdam, 1098 XG, Netherlands"],"raw_orcid":"https://orcid.org/0000-0002-4429-6531","affiliations":[{"raw_affiliation_string":"Department of Stochastics, Centrum Wiskunde & Informatica, Science Park 123, Amsterdam, 1098 XG, Netherlands","institution_ids":["https://openalex.org/I1341640284"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026617038","display_name":"Sandjai Bhulai","orcid":"https://orcid.org/0000-0003-1124-8821"},"institutions":[{"id":"https://openalex.org/I865915315","display_name":"Vrije Universiteit Amsterdam","ror":"https://ror.org/008xxew50","country_code":"NL","type":"education","lineage":["https://openalex.org/I865915315"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Sandjai Bhulai","raw_affiliation_strings":["Department of Mathematics, Vrije Universiteit, De Boelelaan 1111, Amsterdam, 1081 HV, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Vrije Universiteit, De Boelelaan 1111, Amsterdam, 1081 HV, Netherlands","institution_ids":["https://openalex.org/I865915315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065053049","display_name":"Rob van der Mei","orcid":"https://orcid.org/0000-0002-5685-5310"},"institutions":[{"id":"https://openalex.org/I1341640284","display_name":"Centrum Wiskunde & Informatica","ror":"https://ror.org/00x7ekv49","country_code":"NL","type":"facility","lineage":["https://openalex.org/I1341640284","https://openalex.org/I2800991832","https://openalex.org/I4405262988"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Rob van der Mei","raw_affiliation_strings":["Department of Stochastics, Centrum Wiskunde & Informatica, Science Park 123, Amsterdam, 1098 XG, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Stochastics, Centrum Wiskunde & Informatica, Science Park 123, Amsterdam, 1098 XG, Netherlands","institution_ids":["https://openalex.org/I1341640284"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5001885546"],"corresponding_institution_ids":["https://openalex.org/I1341640284"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07780144,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"53","issue":"21","first_page":"24689","last_page":"24708"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9983999729156494,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9980999827384949,"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/pairwise-comparison","display_name":"Pairwise comparison","score":0.9497077465057373},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8299450278282166},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5846380591392517},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5820719003677368},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5609230995178223},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.45433005690574646},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4077838063240051},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1328439712524414}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.9497077465057373},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8299450278282166},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5846380591392517},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5820719003677368},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5609230995178223},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.45433005690574646},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4077838063240051},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1328439712524414},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s10489-023-04516-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-023-04516-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-04516-5.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:cwi.nl:33282","is_oa":true,"landing_page_url":"https://ir.cwi.nl/pub/33282","pdf_url":"https://ir.cwi.nl/pub/33282/33282.pdf","source":{"id":"https://openalex.org/S7407055335","display_name":"Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands","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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Intelligence","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:research.vu.nl:openaire/85f0a296-b0ec-4cdd-95f7-52e8b5591a91","is_oa":true,"landing_page_url":"https://hdl.handle.net/1871.1/85f0a296-b0ec-4cdd-95f7-52e8b5591a91","pdf_url":null,"source":{"id":"https://openalex.org/S4306401107","display_name":"VU Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I865915315","host_organization_name":"Vrije Universiteit Amsterdam","host_organization_lineage":["https://openalex.org/I865915315"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Pries, J, Bhulai, S & van der Mei, R 2023, 'Active pairwise distance learning for efficient labeling of large datasets by human experts', Applied Intelligence, vol. 53, no. 21, pp. 24689-24708. https://doi.org/10.1007/s10489-023-04516-5","raw_type":"article"},{"id":"pmh:oai:research.vu.nl:openaire_cris_publications/85f0a296-b0ec-4cdd-95f7-52e8b5591a91","is_oa":true,"landing_page_url":"https://research.vu.nl/en/publications/85f0a296-b0ec-4cdd-95f7-52e8b5591a91","pdf_url":null,"source":{"id":"https://openalex.org/S4306401107","display_name":"VU Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I865915315","host_organization_name":"Vrije Universiteit Amsterdam","host_organization_lineage":["https://openalex.org/I865915315"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Pries, J, Bhulai, S & van der Mei, R 2023, 'Active pairwise distance learning for efficient labeling of large datasets by human experts', Applied Intelligence, vol. 53, no. 21, pp. 24689-24708. https://doi.org/10.1007/s10489-023-04516-5","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s10489-023-04516-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-023-04516-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-04516-5.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6100000143051147,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385341770.pdf","grobid_xml":"https://content.openalex.org/works/W4385341770.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1479807131","https://openalex.org/W1841961408","https://openalex.org/W1888898201","https://openalex.org/W1951304353","https://openalex.org/W1972098431","https://openalex.org/W1972969203","https://openalex.org/W2033736278","https://openalex.org/W2065383075","https://openalex.org/W2068042582","https://openalex.org/W2096733369","https://openalex.org/W2102705755","https://openalex.org/W2125464731","https://openalex.org/W2130473611","https://openalex.org/W2141245797","https://openalex.org/W2295256067","https://openalex.org/W2295987691","https://openalex.org/W2323180518","https://openalex.org/W2404287519","https://openalex.org/W2884586244","https://openalex.org/W2956371155","https://openalex.org/W3041133507","https://openalex.org/W3110318438","https://openalex.org/W3205626500","https://openalex.org/W4226289437","https://openalex.org/W6601215536"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W2942366970","https://openalex.org/W2793211469","https://openalex.org/W2949152769","https://openalex.org/W4372354731","https://openalex.org/W2562400057","https://openalex.org/W1692008701","https://openalex.org/W2597588799","https://openalex.org/W4360593462","https://openalex.org/W2194570607"],"abstract_inverted_index":{"Abstract":[0],"In":[1,156],"many":[2,176],"machine":[3],"learning":[4,62],"applications,":[5],"the":[6,27,36,45,56,65,71,114,138,151,154,171,183,189,206,213,220],"labeling":[7],"of":[8,21,35,49,58,119,133,153,223],"datasets":[9],"is":[10,16,48,67,123,135,142],"done":[11],"by":[12,39],"human":[13,37],"experts,":[14],"which":[15,44,83],"usually":[17],"time-consuming":[18],"in":[19,199],"cases":[20],"large":[22],"data":[23],"sets.":[24],"This":[25,53],"raises":[26],"need":[28],"for":[29,43,101,170],"methods":[30],"to":[31,68,92,127,137,143,195],"make":[32,128],"optimal":[33],"use":[34],"expert":[38,46,112],"selecting":[40],"model":[41],"instances":[42,134],"opinion":[47],"most":[50],"added":[51],"value.":[52],"paper":[54],"introduces":[55],"problem":[57],"active":[59],"pairwise":[60,72,147,172,221],"distance":[61,78,115],"(APDL),":[63],"where":[64],"goal":[66],"actively":[69],"learn":[70],"distances":[73,173,222],"between":[74,95,99,116],"all":[75,146],"instances.":[76,120],"Any":[77],"function":[79,196],"can":[80,88,227],"be":[81,90,228],"used,":[82],"means":[84],"that":[85,204],"APDL":[86],"techniques":[87],"e.g.,":[89],"used":[91],"determine":[93],"likeness":[94],"faces":[96],"or":[97],"similarities":[98],"users":[100],"recommender":[102],"systems.":[103],"Starting":[104],"with":[105],"an":[106,111,124,167],"unlabeled":[107],"dataset,":[108],"each":[109,129],"round":[110],"determines":[113],"one":[117],"pair":[118],"Thus,":[121],"there":[122],"important":[125],"choice":[126],"round:":[130],"\u2018Which":[131],"combination":[132],"presented":[136],"expert?\u2019":[139],"The":[140,180],"objective":[141],"accurately":[144],"predict":[145],"distances,":[148],"while":[149],"minimizing":[150],"usage":[152],"expert.":[155],"this":[157,218],"research,":[158],"we":[159],"establish":[160],"upper":[161],"and":[162,174,188],"lower":[163],"bound":[164],"approximations":[165],"(including":[166],"update":[168],"rule)":[169],"evaluate":[175],"domain-independent":[177],"query":[178],"strategies.":[179,215],"observations":[181],"from":[182],"experiments":[184],"are":[185,192],"therefore":[186],"general,":[187],"selection":[190],"strategies":[191],"ideal":[193],"candidates":[194],"as":[197],"baseline":[198],"future":[200],"research.":[201],"We":[202],"show":[203],"using":[205,217],"criterion":[207],"max":[208],"degree":[209],"consistently":[210],"ranks":[211],"amongst":[212],"best":[214],"By":[216],"criterion,":[219],"a":[224],"new":[225],"dataset":[226],"labeled":[229],"much":[230],"more":[231],"efficiently.":[232]},"counts_by_year":[],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}