{"id":"https://openalex.org/W4415884135","doi":"https://doi.org/10.1109/icpm66919.2025.11220704","title":"Discovering Stochastic Causal Nets","display_name":"Discovering Stochastic Causal Nets","publication_year":2025,"publication_date":"2025-10-20","ids":{"openalex":"https://openalex.org/W4415884135","doi":"https://doi.org/10.1109/icpm66919.2025.11220704"},"language":"en","primary_location":{"id":"doi:10.1109/icpm66919.2025.11220704","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpm66919.2025.11220704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 7th International Conference on Process Mining (ICPM)","raw_type":"proceedings-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/A5070559820","display_name":"Tianrui Li","orcid":"https://orcid.org/0000-0001-7780-104X"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Tian Li","raw_affiliation_strings":["The University of Melbourne, Australia RWTH Aachen University,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Melbourne, Australia RWTH Aachen University,Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088302185","display_name":"Sander J. J. Leemans","orcid":"https://orcid.org/0000-0002-5201-7125"},"institutions":[{"id":"https://openalex.org/I4210096398","display_name":"Fraunhofer Institute for Production Technology IPT","ror":"https://ror.org/00t0rcy29","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210096398","https://openalex.org/I4923324"]},{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sander J.J. Leemans","raw_affiliation_strings":["RWTH Aachen University, Germany Fraunhofer,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RWTH Aachen University, Germany Fraunhofer,Germany","institution_ids":["https://openalex.org/I4210096398","https://openalex.org/I887968799"]}]},{"author_position":"last","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":"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":["The University of Melbourne Parkville, VIC,Australia,3010"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Melbourne Parkville, VIC,Australia,3010","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070559820"],"corresponding_institution_ids":["https://openalex.org/I887968799"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.49695177,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.9829999804496765,"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":0.9829999804496765,"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/T12127","display_name":"Software System Performance and Reliability","score":0.0035000001080334187,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.0010000000474974513,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/formalism","display_name":"Formalism (music)","score":0.6446999907493591},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5216000080108643},{"id":"https://openalex.org/keywords/stochastic-process","display_name":"Stochastic process","score":0.5133000016212463},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5116999745368958},{"id":"https://openalex.org/keywords/process-modeling","display_name":"Process modeling","score":0.46309998631477356},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.4456000030040741},{"id":"https://openalex.org/keywords/stochastic-modelling","display_name":"Stochastic modelling","score":0.39340001344680786},{"id":"https://openalex.org/keywords/process-mining","display_name":"Process mining","score":0.3887999951839447}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6771000027656555},{"id":"https://openalex.org/C73301696","wikidata":"https://www.wikidata.org/wiki/Q5469984","display_name":"Formalism (music)","level":3,"score":0.6446999907493591},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5216000080108643},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.5133000016212463},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5116999745368958},{"id":"https://openalex.org/C76956256","wikidata":"https://www.wikidata.org/wiki/Q27610560","display_name":"Process modeling","level":3,"score":0.46309998631477356},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.4456000030040741},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4009000062942505},{"id":"https://openalex.org/C127491075","wikidata":"https://www.wikidata.org/wiki/Q7617825","display_name":"Stochastic modelling","level":2,"score":0.39340001344680786},{"id":"https://openalex.org/C124670913","wikidata":"https://www.wikidata.org/wiki/Q2608526","display_name":"Process mining","level":5,"score":0.3887999951839447},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.3831999897956848},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C85345410","wikidata":"https://www.wikidata.org/wiki/Q851587","display_name":"Business process","level":3,"score":0.37470000982284546},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36820000410079956},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3488999903202057},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33090001344680786},{"id":"https://openalex.org/C93453677","wikidata":"https://www.wikidata.org/wiki/Q1017580","display_name":"Business process discovery","level":5,"score":0.3172999918460846},{"id":"https://openalex.org/C158535547","wikidata":"https://www.wikidata.org/wiki/Q5165437","display_name":"Continuous-time stochastic process","level":3,"score":0.3172999918460846},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3000999987125397},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.295199990272522},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C155214134","wikidata":"https://www.wikidata.org/wiki/Q1120460","display_name":"Communicating sequential processes","level":4,"score":0.2854999899864197}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icpm66919.2025.11220704","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpm66919.2025.11220704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 7th International Conference on Process Mining (ICPM)","raw_type":"proceedings-article"},{"id":"pmh:oai:publica.fraunhofer.de:publica/503288","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/503288","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"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"},{"id":"pmh:oai:publications.rwth-aachen.de:1033885","is_oa":false,"landing_page_url":"https://publications.rwth-aachen.de/record/1033885","pdf_url":null,"source":{"id":"https://openalex.org/S4306401033","display_name":"RWTH Publications (RWTH Aachen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887968799","host_organization_name":"RWTH Aachen University","host_organization_lineage":["https://openalex.org/I887968799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2025 7th International Conference on Process Mining : ICPM 2025 : Montevideo, Uruguay, 20-24 October 2025 : proceedings / editors: Jochen De Weerdt, Jana-Rebecca Rehse, Hajo Reijers ; IEEE Computational Intelligence Society<br/>7. International Conference on Process Mining, ICPM 2025, Montevideo, Uruguay, 2025-10-20 - 2025-10-24","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1509056567","https://openalex.org/W1598385458","https://openalex.org/W2417863416","https://openalex.org/W2607172616","https://openalex.org/W2969679630","https://openalex.org/W3003257820","https://openalex.org/W3096326726","https://openalex.org/W3157808921","https://openalex.org/W4243932450","https://openalex.org/W4323545778","https://openalex.org/W4399273063","https://openalex.org/W4399273109","https://openalex.org/W4401964365","https://openalex.org/W4402836068","https://openalex.org/W4402836076","https://openalex.org/W4408985740","https://openalex.org/W4413839947"],"related_works":[],"abstract_inverted_index":{"Process":[0],"mining":[1],"leverages":[2],"event":[3,37,142],"logs":[4],"extracted":[5],"from":[6,36],"information":[7],"systems":[8],"to":[9,67,73,78,119,133,166],"generate":[10],"insights":[11,19],"into":[12],"the":[13,26,68,75,80,83,127,131,136,140,160,163,169,176],"business":[14],"processes":[15],"of":[16,28,54,82,130,139,162,178],"organizations.":[17],"These":[18,124],"are":[20,41],"enhanced":[21],"by":[22,108],"explicitly":[23],"accounting":[24],"for":[25],"frequency":[27],"behavior":[29],"captured":[30],"in":[31,175],"stochastic":[32,69,90,128,179],"process":[33,45],"models":[34,171],"constructed":[35],"logs.":[38],"Causal":[39],"nets":[40,77],"an":[42],"elegant":[43],"declarative":[44],"modeling":[46,55],"formalism":[47,66],"that":[48,71],"relies":[49],"on":[50,156],"a":[51,89,102,109],"small":[52],"number":[53],"constructs,":[56],"yet":[57],"is":[58],"expressive.":[59],"In":[60],"this":[61,65,157],"paper,":[62],"we":[63],"extend":[64],"setting,":[70],"is,":[72],"allow":[74],"extended":[76],"capture":[79],"likelihoods":[81],"observed":[84],"process.":[85],"We":[86],"also":[87],"propose":[88],"causal":[91,104],"net":[92,105],"discovery":[93,112],"approach":[94,99],"using":[95],"Markovian":[96,137],"abstraction.":[97],"Our":[98,144],"begins":[100],"with":[101],"standard":[103],"model":[106,132],"generated":[107],"control":[110],"flow":[111],"algorithm,":[113],"and":[114,149],"then":[115],"employs":[116],"optimization":[117],"techniques":[118],"determine":[120],"optimal":[121],"binding":[122],"weights.":[123],"weights":[125],"enable":[126],"interpretation":[129],"closely":[134],"approximate":[135],"abstraction":[138],"original":[141],"log.":[143],"technique":[145],"has":[146],"been":[147],"implemented":[148],"made":[150],"publicly":[151],"available.":[152],"The":[153],"evaluation":[154],"based":[155],"implementation":[158],"demonstrates":[159],"feasibility":[161],"technique.":[164],"Compared":[165],"baseline":[167],"models,":[168],"discovered":[170],"achieve":[172],"noticeable":[173],"improvements":[174],"quality":[177],"conformance.":[180]},"counts_by_year":[],"updated_date":"2026-04-26T08:31:28.666265","created_date":"2025-11-04T00:00:00"}
