{"id":"https://openalex.org/W4221073079","doi":"https://doi.org/10.1007/978-3-030-98581-3_10","title":"Can Deep Neural Networks Learn Process Model Structure? An\u00a0Assessment Framework and\u00a0Analysis","display_name":"Can Deep Neural Networks Learn Process Model Structure? An\u00a0Assessment Framework and\u00a0Analysis","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4221073079","doi":"https://doi.org/10.1007/978-3-030-98581-3_10"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-030-98581-3_10","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-030-98581-3_10","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-030-98581-3_10.pdf","source":{"id":"https://openalex.org/S4210177767","display_name":"Lecture notes in business information processing","issn_l":"1865-1348","issn":["1865-1348","1865-1356"],"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":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Business Information Processing","raw_type":"book-chapter"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/978-3-030-98581-3_10.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025815548","display_name":"Jari Peeperkorn","orcid":"https://orcid.org/0000-0003-4644-4881"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Jari Peeperkorn","raw_affiliation_strings":["Research Center for Information Systems Engineering (LIRIS), KU Leuven, Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Center for Information Systems Engineering (LIRIS), KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001193136","display_name":"Seppe vanden Broucke","orcid":"https://orcid.org/0000-0002-8781-3906"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]},{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Seppe vanden Broucke","raw_affiliation_strings":["Department of Business Informatics and Operations Management, Ghent University, Ghent, Belgium","Research Center for Information Systems Engineering (LIRIS), KU Leuven, Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Business Informatics and Operations Management, Ghent University, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"Research Center for Information Systems Engineering (LIRIS), KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080266755","display_name":"Jochen De Weerdt","orcid":"https://orcid.org/0000-0001-6151-0504"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Jochen De Weerdt","raw_affiliation_strings":["Research Center for Information Systems Engineering (LIRIS), KU Leuven, Leuven, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Center for Information Systems Engineering (LIRIS), KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5025815548"],"corresponding_institution_ids":["https://openalex.org/I99464096"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"127","last_page":"139"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.9987000226974487,"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":0.9987000226974487,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9768999814987183,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9545000195503235,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8138331174850464},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7821919918060303},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7299860119819641},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6808423399925232},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.598637580871582},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5853217840194702},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5721144676208496},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5646213293075562},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46828219294548035},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.46821048855781555},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09583225846290588}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8138331174850464},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7821919918060303},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7299860119819641},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6808423399925232},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.598637580871582},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5853217840194702},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5721144676208496},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5646213293075562},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46828219294548035},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.46821048855781555},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09583225846290588},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/978-3-030-98581-3_10","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-030-98581-3_10","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-030-98581-3_10.pdf","source":{"id":"https://openalex.org/S4210177767","display_name":"Lecture notes in business information processing","issn_l":"1865-1348","issn":["1865-1348","1865-1356"],"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":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Business Information Processing","raw_type":"book-chapter"},{"id":"pmh:oai:arXiv.org:2202.11985","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2202.11985","pdf_url":"https://arxiv.org/pdf/2202.11985","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"pmh:oai:archive.ugent.be:8751963","is_oa":true,"landing_page_url":"https://biblio.ugent.be/publication/8751963","pdf_url":null,"source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"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":"ISBN: 9783030985813","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.1007/978-3-030-98581-3_10","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-030-98581-3_10","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-030-98581-3_10.pdf","source":{"id":"https://openalex.org/S4210177767","display_name":"Lecture notes in business information processing","issn_l":"1865-1348","issn":["1865-1348","1865-1356"],"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":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Business Information Processing","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4221073079.pdf","grobid_xml":"https://content.openalex.org/works/W4221073079.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1604264128","https://openalex.org/W2067619114","https://openalex.org/W2095705004","https://openalex.org/W2122825543","https://openalex.org/W2581522324","https://openalex.org/W2584722588","https://openalex.org/W2766196653","https://openalex.org/W2907083156","https://openalex.org/W2944716568","https://openalex.org/W2969940319","https://openalex.org/W2995216404","https://openalex.org/W3022806883","https://openalex.org/W3091710143","https://openalex.org/W3140537353","https://openalex.org/W4288356450","https://openalex.org/W4288560456","https://openalex.org/W4302375066","https://openalex.org/W4385245566","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W3099765033","https://openalex.org/W3008584592"],"abstract_inverted_index":{"Abstract":[0],"Predictive":[1],"process":[2,79,122,131,165],"monitoring":[3],"concerns":[4],"itself":[5],"with":[6,103,133],"the":[7,75,114,138],"prediction":[8],"of":[9,77,116,140,154],"ongoing":[10],"cases":[11],"in":[12,43,60,94],"(business)":[13],"processes.":[14],"Prediction":[15],"tasks":[16,42],"typically":[17],"focus":[18],"on":[19,66,137],"remaining":[20],"time,":[21],"outcome,":[22],"next":[23],"event":[24],"or":[25,91],"full":[26],"case":[27],"suffix":[28],"prediction.":[29,142],"Various":[30],"methods":[31],"using":[32],"machine":[33],"and":[34,107],"deep":[35,117],"learning":[36,118],"have":[37,58],"been":[38],"proposed":[39],"for":[40,148],"these":[41,161],"recent":[44],"years.":[45],"Especially":[46],"recurrent":[47],"neural":[48,69,85],"networks":[49,86],"(RNNs)":[50],"such":[51,68,84,149],"as":[52],"long":[53],"short-term":[54],"memory":[55],"nets":[56],"(LSTMs)":[57],"gained":[59],"popularity.":[61],"However,":[62],"no":[63],"research":[64],"focuses":[65],"whether":[67],"network-based":[70],"models":[71,119,132,162],"can":[72,83],"truly":[73],"learn":[74,88,121,164],"structure":[76],"underlying":[78],"models.":[80],"For":[81],"instance,":[82],"effectively":[87],"parallel":[89],"behaviour":[90],"loops?":[92],"Therefore,":[93],"this":[95,127],"work,":[96],"we":[97],"propose":[98],"an":[99],"evaluation":[100],"scheme":[101],"complemented":[102],"new":[104],"fitness,":[105],"precision,":[106],"generalisation":[108],"metrics,":[109],"specifically":[110],"tailored":[111],"towards":[112],"measuring":[113],"capacity":[115],"to":[120,129,159,163],"model":[123,166],"structure.":[124,167],"We":[125],"apply":[126],"framework":[128],"several":[130],"simple":[134],"control-flow":[135],"behaviour,":[136],"task":[139],"next-event":[141],"Our":[143],"results":[144],"show":[145],"that,":[146],"even":[147],"simplistic":[150],"models,":[151],"careful":[152],"tuning":[153],"overfitting":[155],"countermeasures":[156],"is":[157],"required":[158],"allow":[160]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2022-04-03T00:00:00"}
