{"id":"https://openalex.org/W4415360940","doi":"https://doi.org/10.1007/s44311-025-00027-3","title":"Generalization estimation in process mining: the impact of event data quality","display_name":"Generalization estimation in process mining: the impact of event data quality","publication_year":2025,"publication_date":"2025-10-20","ids":{"openalex":"https://openalex.org/W4415360940","doi":"https://doi.org/10.1007/s44311-025-00027-3"},"language":"en","primary_location":{"id":"doi:10.1007/s44311-025-00027-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44311-025-00027-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44311-025-00027-3.pdf","source":{"id":"https://openalex.org/S5407036648","display_name":"Process Science","issn_l":"2948-2178","issn":["2948-2178"],"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":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Process Science","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/s44311-025-00027-3.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107530878","display_name":"Anandi Karunaratne","orcid":null},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Anandi Karunaratne","raw_affiliation_strings":["School of Computing and Information Systems, The University of Melbourne, Melbourne, Victoria, 3010, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Information Systems, The University of Melbourne, Melbourne, Victoria, 3010, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024929895","display_name":"Artem Polyvyanyy","orcid":"https://orcid.org/0000-0002-7672-1643"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Artem Polyvyanyy","raw_affiliation_strings":["School of Computing and Information Systems, The University of Melbourne, Melbourne, Victoria, 3010, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Information Systems, The University of Melbourne, Melbourne, Victoria, 3010, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081861848","display_name":"Alistair Moffat","orcid":"https://orcid.org/0000-0002-6638-0232"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Alistair Moffat","raw_affiliation_strings":["School of Computing and Information Systems, The University of Melbourne, Melbourne, Victoria, 3010, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Information Systems, The University of Melbourne, Melbourne, Victoria, 3010, Australia","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5107530878"],"corresponding_institution_ids":["https://openalex.org/I165779595"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44297672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10679","display_name":"Service-Oriented Architecture and Web Services","score":0.9886999726295471,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9765999913215637,"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/representativeness-heuristic","display_name":"Representativeness heuristic","score":0.8034999966621399},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6844000220298767},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.621399998664856},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5967000126838684},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.5008000135421753},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4853000044822693},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.42879998683929443},{"id":"https://openalex.org/keywords/event-data","display_name":"Event data","score":0.33959999680519104}],"concepts":[{"id":"https://openalex.org/C37381756","wikidata":"https://www.wikidata.org/wiki/Q20203288","display_name":"Representativeness heuristic","level":2,"score":0.8034999966621399},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6844000220298767},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.621399998664856},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6171000003814697},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.597000002861023},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5967000126838684},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.5008000135421753},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4853000044822693},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.42879998683929443},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3425999879837036},{"id":"https://openalex.org/C2987896495","wikidata":"https://www.wikidata.org/wiki/Q5416716","display_name":"Event data","level":3,"score":0.33959999680519104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3352999985218048},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3082999885082245},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C76956256","wikidata":"https://www.wikidata.org/wiki/Q27610560","display_name":"Process modeling","level":3,"score":0.2551000118255615},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s44311-025-00027-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44311-025-00027-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44311-025-00027-3.pdf","source":{"id":"https://openalex.org/S5407036648","display_name":"Process Science","issn_l":"2948-2178","issn":["2948-2178"],"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":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Process Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s44311-025-00027-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44311-025-00027-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44311-025-00027-3.pdf","source":{"id":"https://openalex.org/S5407036648","display_name":"Process Science","issn_l":"2948-2178","issn":["2948-2178"],"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":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Process Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2248501085","display_name":"Embedding Enterprise Systems in IoT Fog Networks through Microservices","funder_award_id":"DP220101516","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4415360940.pdf"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1494072022","https://openalex.org/W1977090757","https://openalex.org/W2001862417","https://openalex.org/W2002994249","https://openalex.org/W2030874315","https://openalex.org/W2038057323","https://openalex.org/W2047246003","https://openalex.org/W2079344889","https://openalex.org/W2092898466","https://openalex.org/W2103336148","https://openalex.org/W2109837661","https://openalex.org/W2111207692","https://openalex.org/W2113987092","https://openalex.org/W2114413252","https://openalex.org/W2171783890","https://openalex.org/W2476917595","https://openalex.org/W2503067222","https://openalex.org/W2508787983","https://openalex.org/W2524473748","https://openalex.org/W2789615162","https://openalex.org/W2903435243","https://openalex.org/W2903974159","https://openalex.org/W2955128005","https://openalex.org/W2990109202","https://openalex.org/W3013065916","https://openalex.org/W3090577282","https://openalex.org/W3094388958","https://openalex.org/W3123060036","https://openalex.org/W3179756580","https://openalex.org/W4230145224","https://openalex.org/W4249433740","https://openalex.org/W4294816253","https://openalex.org/W4402836103","https://openalex.org/W4405922947","https://openalex.org/W6910361653","https://openalex.org/W6927106720","https://openalex.org/W6948214015"],"related_works":[],"abstract_inverted_index":{"The":[0],"problem":[1],"of":[2,34,52,101,227,253,274,285],"process":[3,6,10,260],"discovery":[4,261],"in":[5],"mining":[7],"involves":[8],"constructing":[9],"models":[11,36],"from":[12,197,250],"event":[13,61,78,86,151],"data":[14,152],"to":[15,26,66,95,149,188,194],"describe":[16],"real-world":[17],"systems":[18,25,232],"that":[19,125,158,265],"generated":[20],"the":[21,53,56,93,99,172,198,206,225,266],"data,":[22],"allowing":[23],"those":[24],"be":[27,64],"studied":[28],"and":[29,49,143,145,211,233,282],"improved.":[30],"One":[31],"quality":[32],"criterion":[33],"discovered":[35],"is":[37,59,133,146],"generalization":[38,102,108,163,212,287],",":[39],"which":[40,81,96],"assesses":[41],"how":[42,83],"well":[43,84],"a":[44,110,118,136,237],"model":[45,114,176],"describes":[46],"both":[47],"seen":[48],"unseen":[50],"processes":[51],"system.":[54],"When":[55],"system":[57,173,218],"itself":[58],"unknown,":[60],"logs":[62,168,181,191],"must":[63],"used":[65],"determine":[67],"model-system":[68,275],"relationships,":[69],"such":[70],"as":[71,109],"generalization.":[72,255],"In":[73],"this":[74,243],"work,":[75],"we":[76,235,263],"investigate":[77],"log":[79,87,123,159,209],"representativeness,":[80],"measures":[82],"an":[85],"reflects":[88],"its":[89,141],"generative":[90],"system,":[91],"exploring":[92],"extent":[94],"representativeness":[97,124,160,210],"affects":[98,162],"accuracy":[100],"estimation.":[103],"Our":[104,154,201],"research":[105,281],"employs":[106],"bootstrap":[107,254,267,286],"method":[111,268],"for":[112,122,174,241],"estimating":[113],"generalization,":[115,177],"complemented":[116],"by":[117],"novel":[119],"approximation":[120,132],"technique":[121],"correlates":[126],"strongly":[127],"with":[128],"previous":[129],"measures.":[130],"This":[131],"validated":[134],"through":[135],"ground":[137,199],"truth":[138],"analysis,":[139],"demonstrating":[140,224],"robustness":[142],"accuracy,":[144],"also":[147],"applicable":[148],"various":[150],"types.":[153],"extensive":[155],"experiments":[156],"show":[157,264],"substantially":[161],"estimation":[164],"accuracy:":[165],"highly":[166,189],"representative":[167,180,190],"can":[169,192,269],"directly":[170],"represent":[171],"measuring":[175],"while":[178],"less":[179],"require":[182],"additional":[183],"estimations.":[184],"Interestingly,":[185],"applying":[186],"estimations":[187,219],"lead":[193],"further":[195],"deviations":[196],"truth.":[200],"findings":[202,229],"offer":[203],"insights":[204],"into":[205],"relationship":[207],"between":[208],"estimation,":[213],"identifying":[214],"specific":[215],"regions":[216],"where":[217],"are":[220],"most":[221],"beneficial.":[222],"By":[223],"consistency":[226],"our":[228,251],"across":[230],"multiple":[231],"scenarios,":[234],"provide":[236],"more":[238,271],"robust":[239],"framework":[240],"understanding":[242],"relationship.":[244],"A":[245],"key":[246],"theoretical":[247],"contribution":[248],"emerges":[249],"investigation":[252],"Under":[256],"reasonable":[257],"assumptions":[258],"about":[259],"techniques,":[262],"yield":[270],"precise":[272],"estimates":[273],"precision":[276],"than":[277],"recall,":[278],"guiding":[279],"future":[280],"practical":[283],"applications":[284],"method.":[288]},"counts_by_year":[],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-21T00:00:00"}