{"id":"https://openalex.org/W1994445591","doi":"https://doi.org/10.1109/tkde.2014.2365780","title":"Graph-Based Approaches for Over-Sampling in the Context of Ordinal Regression","display_name":"Graph-Based Approaches for Over-Sampling in the Context of Ordinal Regression","publication_year":2014,"publication_date":"2014-10-30","ids":{"openalex":"https://openalex.org/W1994445591","doi":"https://doi.org/10.1109/tkde.2014.2365780","mag":"1994445591"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2014.2365780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2014.2365780","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","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/A5065093980","display_name":"Mar\u00eda P\u00e9rez\u2010Ortiz","orcid":"https://orcid.org/0000-0003-1302-6093"},"institutions":[{"id":"https://openalex.org/I53110688","display_name":"University of C\u00f3rdoba","ror":"https://ror.org/05yc77b46","country_code":"ES","type":"education","lineage":["https://openalex.org/I53110688"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Maria Perez-Ortiz","raw_affiliation_strings":["Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Campus de Rabanales, C2 building, 14004\u2014C\u00f3rdoba, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Campus de Rabanales, C2 building, 14004\u2014C\u00f3rdoba, Spain","institution_ids":["https://openalex.org/I53110688"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063964437","display_name":"Pedro Antonio Guti\u00e9rrez","orcid":"https://orcid.org/0000-0002-2657-776X"},"institutions":[{"id":"https://openalex.org/I53110688","display_name":"University of C\u00f3rdoba","ror":"https://ror.org/05yc77b46","country_code":"ES","type":"education","lineage":["https://openalex.org/I53110688"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Pedro Antonio Gutierrez","raw_affiliation_strings":["Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Campus de Rabanales, C2 building, 14004\u2014C\u00f3rdoba, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Campus de Rabanales, C2 building, 14004\u2014C\u00f3rdoba, Spain","institution_ids":["https://openalex.org/I53110688"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086980043","display_name":"C\u00e9sar Herv\u00e1s\u2010Mart\u00ednez","orcid":"https://orcid.org/0000-0003-4564-1816"},"institutions":[{"id":"https://openalex.org/I53110688","display_name":"University of C\u00f3rdoba","ror":"https://ror.org/05yc77b46","country_code":"ES","type":"education","lineage":["https://openalex.org/I53110688"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Cesar Hervas-Martinez","raw_affiliation_strings":["Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Campus de Rabanales, C2 building, 14004\u2014C\u00f3rdoba, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Numerical Analysis, University of C\u00f3rdoba, Campus de Rabanales, C2 building, 14004\u2014C\u00f3rdoba, Spain","institution_ids":["https://openalex.org/I53110688"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100635494","display_name":"Xin Yao","orcid":"https://orcid.org/0000-0001-8837-4442"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xin Yao","raw_affiliation_strings":["Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA) School of Computer Science, University of Birmingham, Birmingham B15 2TT, United Kingdom","Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA), School of Computer Science, University of Birmingham, Birmingham B15 2TT, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA) School of Computer Science, University of Birmingham, Birmingham B15 2TT, United Kingdom","institution_ids":["https://openalex.org/I79619799"]},{"raw_affiliation_string":"Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA), School of Computer Science, University of Birmingham, Birmingham B15 2TT, United Kingdom","institution_ids":["https://openalex.org/I79619799"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5065093980"],"corresponding_institution_ids":["https://openalex.org/I53110688"],"apc_list":null,"apc_paid":null,"fwci":7.1885,"has_fulltext":false,"cited_by_count":61,"citation_normalized_percentile":{"value":0.96945196,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"27","issue":"5","first_page":"1233","last_page":"1245"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","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/T11652","display_name":"Imbalanced Data Classification Techniques","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/T11550","display_name":"Text and Document Classification Technologies","score":0.9955000281333923,"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":0.992900013923645,"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/ordinal-regression","display_name":"Ordinal regression","score":0.9147441387176514},{"id":"https://openalex.org/keywords/ordinal-optimization","display_name":"Ordinal optimization","score":0.713143527507782},{"id":"https://openalex.org/keywords/ordinal-data","display_name":"Ordinal data","score":0.7062664031982422},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5936283469200134},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5893868207931519},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5398103594779968},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5202378034591675},{"id":"https://openalex.org/keywords/ordinal-scale","display_name":"Ordinal Scale","score":0.519499659538269},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48247984051704407},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.45365655422210693},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4422323405742645},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4351325035095215},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4146472215652466},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4133499562740326},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3520405888557434},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32616662979125977},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3097175359725952},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.20486491918563843}],"concepts":[{"id":"https://openalex.org/C110313322","wikidata":"https://www.wikidata.org/wiki/Q7100793","display_name":"Ordinal regression","level":2,"score":0.9147441387176514},{"id":"https://openalex.org/C81386100","wikidata":"https://www.wikidata.org/wiki/Q7100792","display_name":"Ordinal optimization","level":3,"score":0.713143527507782},{"id":"https://openalex.org/C85461838","wikidata":"https://www.wikidata.org/wiki/Q7100785","display_name":"Ordinal data","level":2,"score":0.7062664031982422},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5936283469200134},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5893868207931519},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5398103594779968},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5202378034591675},{"id":"https://openalex.org/C2909711754","wikidata":"https://www.wikidata.org/wiki/Q7100785","display_name":"Ordinal Scale","level":2,"score":0.519499659538269},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48247984051704407},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.45365655422210693},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4422323405742645},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4351325035095215},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4146472215652466},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4133499562740326},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3520405888557434},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32616662979125977},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3097175359725952},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20486491918563843},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tkde.2014.2365780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2014.2365780","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/33198a74-144f-46e1-80be-dc18ac61237a","is_oa":false,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/33198a74-144f-46e1-80be-dc18ac61237a","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"P\u00e9rez-Ortiz, M, Guti\u00e9rrez, P A, Herv\u00e1s-Mart\u00ednez, C & Yao, X 2015, 'Graph-based approaches for over-sampling in the context of ordinal regression', IEEE Transactions on Knowledge and Data Engineering, vol. 27, no. 5, 6940273, pp. 1233-1245. https://doi.org/10.1109/TKDE.2014.2365780","raw_type":"article"},{"id":"pmh:oai:pure.atira.dk:publications/33198a74-144f-46e1-80be-dc18ac61237a","is_oa":false,"landing_page_url":"https://research.birmingham.ac.uk/portal/en/publications/graphbased-approaches-for-oversampling-in-the-context-of-ordinal-regression(33198a74-144f-46e1-80be-dc18ac61237a).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"P\u00e9rez-Ortiz , M , Guti\u00e9rrez , P A , Herv\u00e1s-Mart\u00ednez , C & Yao , X 2015 , ' Graph-based approaches for over-sampling in the context of ordinal regression ' , IEEE Transactions on Knowledge and Data Engineering , vol. 27 , no. 5 , 6940273 , pp. 1233-1245 . https://doi.org/10.1109/TKDE.2014.2365780","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2459667701","display_name":null,"funder_award_id":"P11-TIC-7508","funder_id":"https://openalex.org/F4320326754","funder_display_name":"Junta de Andaluc\u00eda"},{"id":"https://openalex.org/G6794522244","display_name":null,"funder_award_id":"EP/J017515/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8385396385","display_name":"DAASE: Dynamic Adaptive Automated Software Engineering","funder_award_id":"EP/J017515/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320310967","display_name":"Universidad de Sevilla","ror":"https://ror.org/03yxnpp24"},{"id":"https://openalex.org/F4320323834","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449"},{"id":"https://openalex.org/F4320326754","display_name":"Junta de Andaluc\u00eda","ror":"https://ror.org/01jem9c82"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W70001371","https://openalex.org/W188694065","https://openalex.org/W1563088657","https://openalex.org/W1565746575","https://openalex.org/W1941659294","https://openalex.org/W1973003130","https://openalex.org/W1980437782","https://openalex.org/W1980896222","https://openalex.org/W1989368986","https://openalex.org/W2000642020","https://openalex.org/W2006293846","https://openalex.org/W2009205281","https://openalex.org/W2024223694","https://openalex.org/W2035750819","https://openalex.org/W2058475745","https://openalex.org/W2071715137","https://openalex.org/W2080149223","https://openalex.org/W2083551746","https://openalex.org/W2087240369","https://openalex.org/W2099454382","https://openalex.org/W2118978333","https://openalex.org/W2119821739","https://openalex.org/W2122111042","https://openalex.org/W2124105163","https://openalex.org/W2124685890","https://openalex.org/W2124710650","https://openalex.org/W2140187489","https://openalex.org/W2142575165","https://openalex.org/W2143747826","https://openalex.org/W2147232804","https://openalex.org/W2148143831","https://openalex.org/W2169528473","https://openalex.org/W3011144947","https://openalex.org/W4239510810","https://openalex.org/W6633774736","https://openalex.org/W6678181790","https://openalex.org/W6680680495","https://openalex.org/W6680821758"],"related_works":["https://openalex.org/W3021328243","https://openalex.org/W2051517726","https://openalex.org/W66181126","https://openalex.org/W2093964375","https://openalex.org/W2166716405","https://openalex.org/W2023060082","https://openalex.org/W2506242593","https://openalex.org/W4236508908","https://openalex.org/W3092459516","https://openalex.org/W1980208714"],"abstract_inverted_index":{"The":[0,102,115],"classification":[1,19,48,149],"of":[2,49,63,98,125,133,145,153,159],"patterns":[3],"into":[4,76],"naturally":[5],"ordered":[6],"labels":[7],"is":[8,21,83,164],"referred":[9],"to":[10,57,94],"as":[11],"ordinal":[12,15,53,65,80,106,128,161],"regression":[13,129,162],"or":[14],"classification.":[16],"Usually,":[17],"this":[18,86,119],"setting":[20],"by":[22,108],"nature":[23],"highly":[24],"imbalanced,":[25],"because":[26],"there":[27],"are":[28,34],"classes":[29,51],"in":[30,52,61,85,92,118,174],"the":[31,47,64,74,89,96,122,138,143,148,151,160,170],"problem":[32],"that":[33,69],"a":[35,112,126],"priori":[36],"more":[37],"probable":[38],"than":[39],"others.":[40],"Although":[41],"standard":[42],"over-sampling":[43,81,110,171],"methods":[44],"can":[45],"improve":[46,95],"minority":[50,154,179],"classification,":[54],"they":[55,70],"tend":[56],"introduce":[58],"severe":[59],"errors":[60],"terms":[62],"label":[66],"scale,":[67],"given":[68],"do":[71],"not":[72],"take":[73],"ordering":[75,152],"account.":[77],"A":[78,156],"specific":[79],"method":[82,103,130,163],"developed":[84],"paper":[87,120],"for":[88,178],"first":[90],"time":[91],"order":[93],"performance":[97,177],"machine":[99],"learning":[100],"classifiers.":[101],"proposed":[104,140],"includes":[105],"information":[107],"approaching":[109],"from":[111],"graph-based":[113,139],"perspective.":[114],"results":[116],"presented":[117],"show":[121],"good":[123],"synergy":[124],"popular":[127],"(a":[131],"reformulation":[132],"support":[134],"vector":[135],"machines)":[136],"with":[137,169],"algorithms,":[141],"and":[142,150,167],"possibility":[144],"improving":[146],"both":[147],"classes.":[155,180],"cost-sensitive":[157],"version":[158],"also":[165],"introduced":[166],"compared":[168],"proposals,":[172],"showing":[173],"general":[175],"lower":[176]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
