{"id":"https://openalex.org/W4400113319","doi":"https://doi.org/10.1109/mipro60963.2024.10569816","title":"State-of-the-Art Machine Learning Frameworks for Training or Inference on Business Process Dataset","display_name":"State-of-the-Art Machine Learning Frameworks for Training or Inference on Business Process Dataset","publication_year":2024,"publication_date":"2024-05-20","ids":{"openalex":"https://openalex.org/W4400113319","doi":"https://doi.org/10.1109/mipro60963.2024.10569816"},"language":"en","primary_location":{"id":"doi:10.1109/mipro60963.2024.10569816","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mipro60963.2024.10569816","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 47th MIPRO ICT and Electronics Convention (MIPRO)","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/A5099635283","display_name":"M. Kani\u0161ki","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"M. Kani\u0161ki","raw_affiliation_strings":["Faculty of Organization and Informatics,Vara&#x017E;din,Croatia"],"affiliations":[{"raw_affiliation_string":"Faculty of Organization and Informatics,Vara&#x017E;din,Croatia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5099635284","display_name":"S. Kri\u017eani\u0107","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"S. Kri\u017eani\u0107","raw_affiliation_strings":["Faculty of Organization and Informatics,Vara&#x017E;din,Croatia"],"affiliations":[{"raw_affiliation_string":"Faculty of Organization and Informatics,Vara&#x017E;din,Croatia","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5099635283"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12913788,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1865","last_page":"1870"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.9563000202178955,"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":0.9563000202178955,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7567086815834045},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7360355257987976},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6731860041618347},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6524271965026855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5458028316497803},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.5439708828926086},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5221148729324341},{"id":"https://openalex.org/keywords/business-process","display_name":"Business process","score":0.5100660920143127},{"id":"https://openalex.org/keywords/business-process-modeling","display_name":"Business process modeling","score":0.45259523391723633},{"id":"https://openalex.org/keywords/work-in-process","display_name":"Work in process","score":0.24489116668701172},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10126876831054688},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.06977948546409607},{"id":"https://openalex.org/keywords/operations-management","display_name":"Operations management","score":0.05944371223449707}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7567086815834045},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7360355257987976},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6731860041618347},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6524271965026855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5458028316497803},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.5439708828926086},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5221148729324341},{"id":"https://openalex.org/C85345410","wikidata":"https://www.wikidata.org/wiki/Q851587","display_name":"Business process","level":3,"score":0.5100660920143127},{"id":"https://openalex.org/C207505557","wikidata":"https://www.wikidata.org/wiki/Q4374012","display_name":"Business process modeling","level":4,"score":0.45259523391723633},{"id":"https://openalex.org/C174998907","wikidata":"https://www.wikidata.org/wiki/Q357662","display_name":"Work in process","level":2,"score":0.24489116668701172},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10126876831054688},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.06977948546409607},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.05944371223449707},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mipro60963.2024.10569816","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mipro60963.2024.10569816","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 47th MIPRO ICT and Electronics Convention (MIPRO)","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":27,"referenced_works":["https://openalex.org/W2081020307","https://openalex.org/W2104230847","https://openalex.org/W2151554678","https://openalex.org/W2186615578","https://openalex.org/W2194775991","https://openalex.org/W2896484314","https://openalex.org/W2898496135","https://openalex.org/W2908291589","https://openalex.org/W2937479024","https://openalex.org/W2945006551","https://openalex.org/W2958414331","https://openalex.org/W2987728367","https://openalex.org/W3006708286","https://openalex.org/W3098379356","https://openalex.org/W3106099468","https://openalex.org/W3126815129","https://openalex.org/W3155837048","https://openalex.org/W4200543529","https://openalex.org/W4207030261","https://openalex.org/W4210820828","https://openalex.org/W4288540474","https://openalex.org/W4293197619","https://openalex.org/W4295312788","https://openalex.org/W4311653122","https://openalex.org/W6686509673","https://openalex.org/W6713134421","https://openalex.org/W6766978945"],"related_works":["https://openalex.org/W2424740894","https://openalex.org/W2293459815","https://openalex.org/W4300427051","https://openalex.org/W2345053703","https://openalex.org/W2109588827","https://openalex.org/W2130425969","https://openalex.org/W237078725","https://openalex.org/W2005124518","https://openalex.org/W2050159024","https://openalex.org/W2066228984"],"abstract_inverted_index":{"Machine":[0],"learning":[1,18,161],"(ML)":[2],"is":[3,42,137,154,163],"being":[4],"used":[5,164],"to":[6,26,44,95,102,111,120,133,156,200],"solve":[7],"complex":[8],"problems.":[9],"With":[10],"the":[11,21,46,54,58,61,96,105,112,128,134,172,186],"recent":[12],"emergence":[13],"of":[14,23,49,68,98,114,130,141,176],"machine":[15,160],"and":[16,38,60,75,81,87,136,170,174,193],"deep":[17],"(DL)":[19],"architectures,":[20],"number":[22],"available":[24],"frameworks":[25,34,178],"choose":[27],"from":[28,104,149],"has":[29],"also":[30],"increased.":[31],"The":[32,146],"different":[33,36],"have":[35,76,88],"strengths":[37],"weaknesses.":[39],"Therefore,":[40],"it":[41,107],"crucial":[43],"ensure":[45],"highest":[47],"accuracy":[48],"ML/DL":[50,196],"models":[51],"by":[52,159],"choosing":[53,194],"right":[55],"framework":[56,197],"for":[57,79,91,143,165,179],"problem":[59],"data.":[62],"There":[63],"are":[64,72,84,189],"two":[65],"main":[66],"categories":[67],"frameworks.":[69],"Those":[70],"which":[71,83],"feature":[73],"rich":[74],"been":[77,89],"optimized":[78,90],"training,":[80],"those":[82],"fast,":[85],"lightweight,":[86],"inference.":[92,182],"Training":[93],"refers":[94,110],"process":[97,113,125,152],"teaching":[99],"a":[100,116,122,150],"model":[101],"learn":[103],"data":[106,126],"sees.":[108],"Inference":[109],"using":[115],"trained":[117],"machine-learning":[118],"algorithm":[119],"make":[121],"prediction.":[123],"Business":[124],"enables":[127],"monitoring":[129],"events":[131],"related":[132],"system":[135],"an":[138,195],"important":[139,187],"source":[140],"information":[142],"future":[144],"decisions.":[145],"public":[147],"dataset":[148],"business":[151],"that":[153],"ready":[155],"be":[157],"processed":[158],"algorithms":[162],"research.":[166],"This":[167],"paper":[168],"compares":[169],"evaluates":[171],"features":[173],"benefits":[175],"various":[177],"training":[180],"or":[181],"In":[183],"this":[184],"paper,":[185],"metrics":[188],"discussed":[190],"when":[191],"considering":[192],"with":[198],"regard":[199],"its":[201],"limitations.":[202]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
