{"id":"https://openalex.org/W2968918233","doi":"https://doi.org/10.1145/3357385.3357387","title":"Detecting anomalies in hybrid business process logs","display_name":"Detecting anomalies in hybrid business process logs","publication_year":2019,"publication_date":"2019-08-15","ids":{"openalex":"https://openalex.org/W2968918233","doi":"https://doi.org/10.1145/3357385.3357387","mag":"2968918233"},"language":"en","primary_location":{"id":"doi:10.1145/3357385.3357387","doi":"https://doi.org/10.1145/3357385.3357387","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357385.3357387","pdf_url":null,"source":{"id":"https://openalex.org/S4210202865","display_name":"ACM SIGAPP Applied Computing Review","issn_l":"1559-6915","issn":["1559-6915","1931-0161"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","poland-20","russia-white-list-4"],"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGAPP Applied Computing Review","raw_type":"journal-article"},"volume":null,"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/A5076332690","display_name":"Stephen Pauwels","orcid":"https://orcid.org/0000-0002-0427-8945","observed_orcids":["https://orcid.org/0000-0002-0427-8945"]},"institutions":[{"id":"https://openalex.org/I149213910","display_name":"University of Antwerp","ror":"https://ror.org/008x57b05","country_code":"BE","type":"education","lineage":["https://openalex.org/I149213910"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Stephen Pauwels","raw_affiliation_strings":["University of Antwerp, Antwerp, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Antwerp, Antwerp, Belgium","institution_ids":["https://openalex.org/I149213910"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073211270","display_name":"Toon Calders","orcid":"https://orcid.org/0000-0002-4943-6978","observed_orcids":["https://orcid.org/0000-0002-4943-6978"]},"institutions":[{"id":"https://openalex.org/I149213910","display_name":"University of Antwerp","ror":"https://ror.org/008x57b05","country_code":"BE","type":"education","lineage":["https://openalex.org/I149213910"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Toon Calders","raw_affiliation_strings":["University of Antwerp, Antwerp, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Antwerp, Antwerp, Belgium","institution_ids":["https://openalex.org/I149213910"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149213910"],"apc_list":null,"apc_paid":null,"fwci":3.6592,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.9297434,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"19","issue":"2","first_page":"18","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.9765999913215637,"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":0.9765999913215637,"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":0.010700000450015068,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.008500000461935997,"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/business-process-mining","display_name":"business process mining","score":0.6819999814033508},{"id":"https://openalex.org/keywords/dynamic-bayesian-networks","display_name":"dynamic Bayesian networks","score":0.7910000085830688},{"id":"https://openalex.org/keywords/functional-dependencies","display_name":"functional dependencies","score":0.8159999847412109},{"id":"https://openalex.org/keywords/numerical-attributes","display_name":"numerical attributes","score":0.6800000071525574},{"id":"https://openalex.org/keywords/root-cause-analysis","display_name":"root cause analysis","score":0.718999981880188}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8129526376724243},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.6430224180221558},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5930263996124268},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5361637473106384},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5359656810760498},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5244591236114502},{"id":"https://openalex.org/C85345410","wikidata":"https://www.wikidata.org/wiki/Q851587","display_name":"Business process","level":3,"score":0.4850703775882721},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.41270673274993896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3482894003391266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3407450020313263},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.11179661750793457},{"id":"https://openalex.org/C174998907","wikidata":"https://www.wikidata.org/wiki/Q357662","display_name":"Work in process","level":2,"score":0.1104414165019989},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3357385.3357387","doi":"https://doi.org/10.1145/3357385.3357387","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357385.3357387","pdf_url":null,"source":{"id":"https://openalex.org/S4210202865","display_name":"ACM SIGAPP Applied Computing Review","issn_l":"1559-6915","issn":["1559-6915","1931-0161"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","poland-20","russia-white-list-4"],"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGAPP Applied Computing Review","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W14760367","https://openalex.org/W107204879","https://openalex.org/W1738124305","https://openalex.org/W1824971879","https://openalex.org/W1995875735","https://openalex.org/W2037269865","https://openalex.org/W2038819732","https://openalex.org/W2041404167","https://openalex.org/W2094138658","https://openalex.org/W2099111195","https://openalex.org/W2105130030","https://openalex.org/W2121717903","https://openalex.org/W2122410182","https://openalex.org/W2129905273","https://openalex.org/W2134641333","https://openalex.org/W2142635246","https://openalex.org/W2158722884","https://openalex.org/W2159328231","https://openalex.org/W2200183807","https://openalex.org/W2212928539","https://openalex.org/W2347085041","https://openalex.org/W2538859255","https://openalex.org/W2886629814","https://openalex.org/W2892122211","https://openalex.org/W2943613229","https://openalex.org/W2963880114","https://openalex.org/W2982284349","https://openalex.org/W4212774754"],"related_works":["https://openalex.org/W2943613229","https://openalex.org/W4308513861","https://openalex.org/W4417114888","https://openalex.org/W2792904071","https://openalex.org/W2982284349","https://openalex.org/W3127683449","https://openalex.org/W2538859255","https://openalex.org/W2803416334","https://openalex.org/W2788082405","https://openalex.org/W4360980888"],"abstract_inverted_index":{"Checking":[0],"and":[1,34,121,141],"analyzing":[2],"various":[3],"executions":[4,19,106],"of":[5,23,31,52,57,87,138,151,161,171,179],"different":[6],"Business":[7,195],"Processes":[8,196],"can":[9,99],"be":[10,101],"a":[11,27,39,77,85,88,169,185],"tedious":[12],"task":[13],"as":[14],"the":[15,44,70,73,93,108,127,155,165,172,176,180],"logs":[16],"from":[17,92],"these":[18,53],"may":[20],"contain":[21],"lots":[22],"events,":[24],"each":[25],"with":[26,50,118,187],"(possibly":[28],"large)":[29],"number":[30],"both":[32],"numerical":[33,119],"categorical":[35],"attributes.":[36,54,74],"We":[37,75,182],"developed":[38],"way":[40],"to":[41,83,103,124,167],"automatically":[42],"model":[43,86,98,126,135,163],"behavior":[45,129],"captured":[46],"in":[47,107,131,154,194],"log":[48,89,132,156],"files":[49],"dozens":[51],"The":[55,96,134],"advantage":[56],"our":[58,162,200],"method":[59],"is":[60,81,136,164],"that":[61,80,174,199],"we":[62,113],"do":[63],"not":[64],"need":[65],"any":[66],"prior":[67],"knowledge":[68],"about":[69],"data":[71,94],"or":[72,148],"introduce":[76],"new":[78,149],"algorithm":[79],"able":[82],"learn":[84],"file":[90],"starting":[91],"itself.":[95],"learned":[97],"then":[100],"used":[102],"detect":[104],"anomalous":[105],"data.":[109],"To":[110],"achieve":[111],"this":[112],"extend":[114],"Dynamic":[115],"Bayesian":[116],"Networks":[117],"attributes":[120],"functional":[122],"dependencies":[123],"better":[125],"normal":[128],"found":[130],"files.":[133],"capable":[137],"scoring":[139],"events":[140],"cases,":[142],"even":[143],"when":[144],"previously":[145],"unseen":[146],"values":[147,152],"combinations":[150],"appear":[153],"file.":[157],"An":[158],"important":[159],"benefit":[160],"ability":[166],"give":[168],"decomposition":[170],"score":[173],"indicates":[175],"root":[177],"cause":[178],"anomalies.":[181],"also":[183],"conducted":[184],"comparison":[186],"other":[188,203],"state-of-the-art":[189],"algorithms":[190],"for":[191],"detecting":[192],"anomalies":[193],"which":[197],"shows":[198],"approach":[201],"outperforms":[202],"algorithms.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2019-08-22T00:00:00"}
