{"id":"https://openalex.org/W2000131178","doi":"https://doi.org/10.1145/2339530.2339668","title":"Different slopes for different folks","display_name":"Different slopes for different folks","publication_year":2012,"publication_date":"2012-08-12","ids":{"openalex":"https://openalex.org/W2000131178","doi":"https://doi.org/10.1145/2339530.2339668","mag":"2000131178"},"language":"en","primary_location":{"id":"doi:10.1145/2339530.2339668","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2339530.2339668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},"type":"conference-paper","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/A5074794888","display_name":"Wouter Duivesteijn","orcid":"https://orcid.org/0000-0003-0412-8864"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Wouter Duivesteijn","raw_affiliation_strings":["Leiden University, Leiden, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010293806","display_name":"Ad Feelders","orcid":"https://orcid.org/0000-0003-4525-1949"},"institutions":[{"id":"https://openalex.org/I193662353","display_name":"Utrecht University","ror":"https://ror.org/04pp8hn57","country_code":"NL","type":"education","lineage":["https://openalex.org/I193662353"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ad Feelders","raw_affiliation_strings":["Utrecht University, Utrecht, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Utrecht University, Utrecht, Netherlands","institution_ids":["https://openalex.org/I193662353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062278926","display_name":"Arno Knobbe","orcid":"https://orcid.org/0000-0002-0335-5099"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Arno Knobbe","raw_affiliation_strings":["Leiden University, Leiden, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, Netherlands","institution_ids":["https://openalex.org/I121797337"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"868","last_page":"876"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11106","display_name":"Data Management and Algorithms","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9754999876022339,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/generalization","display_name":"Generalization","score":0.7388859987258911},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.6532869935035706},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6129915714263916},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5851680636405945},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4786035716533661},{"id":"https://openalex.org/keywords/exploratory-analysis","display_name":"Exploratory analysis","score":0.4650349020957947},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.45151710510253906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43957585096359253},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34220993518829346},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.33197277784347534},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2987620234489441},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.06645926833152771}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7388859987258911},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.6532869935035706},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6129915714263916},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5851680636405945},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4786035716533661},{"id":"https://openalex.org/C3018260909","wikidata":"https://www.wikidata.org/wiki/Q1322871","display_name":"Exploratory analysis","level":2,"score":0.4650349020957947},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.45151710510253906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43957585096359253},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34220993518829346},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.33197277784347534},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2987620234489441},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.06645926833152771},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2339530.2339668","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2339530.2339668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W11688660","https://openalex.org/W1525766717","https://openalex.org/W1531520279","https://openalex.org/W1983350937","https://openalex.org/W1992129502","https://openalex.org/W1998221592","https://openalex.org/W1998613841","https://openalex.org/W2008374161","https://openalex.org/W2084008509","https://openalex.org/W2107617008","https://openalex.org/W2123730855","https://openalex.org/W2128054485","https://openalex.org/W2145147745","https://openalex.org/W2256075884","https://openalex.org/W2314046083","https://openalex.org/W2796514099","https://openalex.org/W3145203756","https://openalex.org/W4214575751","https://openalex.org/W6600398339","https://openalex.org/W6610734598"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W2034959125","https://openalex.org/W2355687852","https://openalex.org/W2621086889"],"abstract_inverted_index":{"Exceptional":[0],"Model":[1],"Mining":[2],"(EMM)":[3],"is":[4,90],"an":[5],"exploratory":[6],"data":[7,28],"analysis":[8],"technique":[9],"that":[10,127],"can":[11,132],"be":[12],"regarded":[13],"as":[14],"a":[15,31,62,93],"generalization":[16],"of":[17,26,67,95,108,141],"subgroup":[18,36],"discovery.":[19],"In":[20,48],"EMM":[21],"we":[22,51],"look":[23],"for":[24,29,56,64],"subgroups":[25,114],"the":[27,35,40,45,65,74,81,106,109,142,148],"which":[30],"model":[32,42,83],"fitted":[33,43],"to":[34,44,54,76,79,84,104,139,153],"differs":[37],"substantially":[38],"from":[39,120],"same":[41],"entire":[46],"dataset.":[47],"this":[49],"paper":[50],"develop":[52],"methods":[53],"mine":[55],"exceptional":[57],"regression":[58,68,82,135,151],"models.":[59],"We":[60,111,124],"propose":[61],"measure":[63],"exceptionality":[66],"models":[69,117,136,152],"(Cook's":[70],"distance),":[71],"and":[72,144],"explore":[73],"possibilities":[75],"avoid":[77],"having":[78],"fit":[80],"each":[85],"candidate":[86],"subgroup.":[87],"The":[88],"algorithm":[89],"evaluated":[91],"on":[92,118,137],"number":[94],"real":[96],"life":[97],"datasets.":[98],"These":[99],"datasets":[100,119],"are":[101,147],"also":[102,125],"used":[103],"illustrate":[105],"results":[107],"algorithm.":[110],"find":[112],"interesting":[113],"with":[115],"deviating":[116],"several":[121],"different":[122],"domains.":[123],"show":[126],"under":[128],"certain":[129],"circumstances":[130],"one":[131],"forego":[133],"fitting":[134],"up":[138],"40%":[140,146],"subgroups,":[143],"these":[145],"relatively":[149],"expensive":[150],"compute.":[154]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
