{"id":"https://openalex.org/W2946932126","doi":"https://doi.org/10.1109/cogsima.2019.8724300","title":"Situation Mining: Event Pattern Mining for Situation Model Induction","display_name":"Situation Mining: Event Pattern Mining for Situation Model Induction","publication_year":2019,"publication_date":"2019-04-01","ids":{"openalex":"https://openalex.org/W2946932126","doi":"https://doi.org/10.1109/cogsima.2019.8724300","mag":"2946932126"},"language":"en","primary_location":{"id":"doi:10.1109/cogsima.2019.8724300","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cogsima.2019.8724300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","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/A5012675934","display_name":"Andrea Salfinger","orcid":"https://orcid.org/0000-0003-4160-3871"},"institutions":[{"id":"https://openalex.org/I121883995","display_name":"Johannes Kepler University of Linz","ror":"https://ror.org/052r2xn60","country_code":"AT","type":"education","lineage":["https://openalex.org/I121883995"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Andrea Salfinger","raw_affiliation_strings":["Department of Cooperative Information Systems, Johannes Kepler University Linz, Linz, Austria"],"affiliations":[{"raw_affiliation_string":"Department of Cooperative Information Systems, Johannes Kepler University Linz, Linz, Austria","institution_ids":["https://openalex.org/I121883995"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5012675934"],"corresponding_institution_ids":["https://openalex.org/I121883995"],"apc_list":null,"apc_paid":null,"fwci":0.42,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.70075312,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"6242","issue":null,"first_page":"17","last_page":"25"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9962000250816345,"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"}},"topics":[{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9962000250816345,"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"}},{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9940000176429749,"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/T11106","display_name":"Data Management and Algorithms","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/computer-science","display_name":"Computer science","score":0.8293626308441162},{"id":"https://openalex.org/keywords/semantic-reasoner","display_name":"Semantic reasoner","score":0.5553367733955383},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5381949543952942},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.4787246882915497},{"id":"https://openalex.org/keywords/complex-event-processing","display_name":"Complex event processing","score":0.47480738162994385},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46681782603263855},{"id":"https://openalex.org/keywords/knowledge-acquisition","display_name":"Knowledge acquisition","score":0.4415058195590973},{"id":"https://openalex.org/keywords/domain-model","display_name":"Domain model","score":0.4253406524658203},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42286187410354614},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4193650782108307},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41196680068969727},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.38868510723114014},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3802529275417328}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8293626308441162},{"id":"https://openalex.org/C9616225","wikidata":"https://www.wikidata.org/wiki/Q3929429","display_name":"Semantic reasoner","level":2,"score":0.5553367733955383},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5381949543952942},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.4787246882915497},{"id":"https://openalex.org/C123606473","wikidata":"https://www.wikidata.org/wiki/Q907918","display_name":"Complex event processing","level":3,"score":0.47480738162994385},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46681782603263855},{"id":"https://openalex.org/C2777220311","wikidata":"https://www.wikidata.org/wiki/Q6423340","display_name":"Knowledge acquisition","level":2,"score":0.4415058195590973},{"id":"https://openalex.org/C92548554","wikidata":"https://www.wikidata.org/wiki/Q2262868","display_name":"Domain model","level":3,"score":0.4253406524658203},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42286187410354614},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4193650782108307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41196680068969727},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.38868510723114014},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3802529275417328},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.0},{"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/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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":1,"locations":[{"id":"doi:10.1109/cogsima.2019.8724300","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cogsima.2019.8724300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321181","display_name":"Austrian Science Fund","ror":"https://ror.org/013tf3c58"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W22685585","https://openalex.org/W1494581921","https://openalex.org/W1500684598","https://openalex.org/W1518565144","https://openalex.org/W1569922297","https://openalex.org/W1592108404","https://openalex.org/W1970772522","https://openalex.org/W1989885144","https://openalex.org/W1995859603","https://openalex.org/W2015434614","https://openalex.org/W2031006328","https://openalex.org/W2031080236","https://openalex.org/W2046273500","https://openalex.org/W2056610886","https://openalex.org/W2079648951","https://openalex.org/W2139644595","https://openalex.org/W2163231988","https://openalex.org/W2165609373","https://openalex.org/W2422525427","https://openalex.org/W2423923236","https://openalex.org/W2516860271","https://openalex.org/W2726475540","https://openalex.org/W2750078217","https://openalex.org/W3095742340","https://openalex.org/W4313205696","https://openalex.org/W6600919609","https://openalex.org/W6634348080","https://openalex.org/W6635436945","https://openalex.org/W6664734992"],"related_works":["https://openalex.org/W2125479495","https://openalex.org/W2012251886","https://openalex.org/W1559202216","https://openalex.org/W1989583491","https://openalex.org/W2150974735","https://openalex.org/W2083849133","https://openalex.org/W2086580554","https://openalex.org/W2170990285","https://openalex.org/W4229675364","https://openalex.org/W2093171718"],"abstract_inverted_index":{"Computational":[0],"situation":[1,11,86,98,109,123,128,139,145,177,181,190,197,217],"assessment":[2],"(SA)":[3],"systems":[4,27],"support":[5],"human":[6,78],"control":[7],"center":[8],"operators":[9],"in":[10,22,34,175],"monitoring,":[12],"i.e.,":[13],"detecting":[14],"and":[15,19,92,187,192],"tracking":[16],"relevant":[17],"object":[18],"event":[20,63],"constellations":[21],"their":[23,84],"observed":[24,144],"environment.":[25],"SA":[26],"frequently":[28],"employ":[29],"deductive":[30],"reasoning":[31],"techniques":[32],"implemented":[33],"Complex":[35],"Event":[36],"Processing":[37],"or":[38],"rule":[39,213],"engines":[40],"to":[41,81,111,166,208],"solve":[42],"this":[43,97],"real-time":[44],"pattern":[45],"recognition":[46],"problem,":[47],"by":[48,131],"matching":[49],"data":[50,114],"sensed":[51],"from":[52,142,158],"the":[53,62,72,159,176,195,211],"monitored":[54],"environment":[55],"against":[56],"templates":[57],"for":[58,107,189,215],"those":[59],"situations,":[60,76,137],"characterizing":[61],"patterns":[64],"of":[65,75,116,136,149,161],"interest.":[66],"Hence,":[67],"they":[68],"require":[69],"explicitly":[70],"formalizing":[71],"sought-after":[73],"types":[74],"demanding":[77],"domain":[79,160],"experts":[80],"conceptually":[82],"model":[83,129],"cognitive":[85],"hypotheses,":[87],"which":[88,126],"represents":[89],"a":[90,121,155,204],"time-consuming":[91],"non-trivial":[93],"task.":[94],"To":[95],"overcome":[96],"knowledge":[99,173,182],"acquisition":[100,130],"bottleneck,":[101],"we":[102],"therefore":[103],"propose":[104],"an":[105],"approach":[106,151],"inductive":[108],"modeling":[110],"leverage":[112],"existing":[113],"sets":[115],"recorded":[117],"situations:":[118],"We":[119],"contribute":[120],"dedicated":[122],"mining":[124,133],"algorithm,":[125],"bootstraps":[127],"automatically":[132],"behavioral":[134],"models":[135,199],"so-called":[138],"evolution":[140,198],"models,":[141],"already":[143],"instances.":[146],"The":[147],"feasibility":[148],"our":[150],"is":[152],"examined":[153],"on":[154],"case":[156],"study":[157],"road":[162],"traffic":[163],"incident":[164],"management,":[165],"demonstrate":[167],"how":[168,194],"it":[169],"turns":[170],"previously":[171],"implicit":[172],"hidden":[174],"instances":[178],"into":[179],"explicit":[180],"that":[183],"can":[184,200],"be":[185,201],"inspected":[186],"queried":[188],"analytics,":[191],"sketch":[193],"derived":[196],"used":[202],"within":[203],"Model-Driven":[205],"Engineering":[206],"framework":[207],"directly":[209],"generate":[210],"corresponding":[212],"code":[214],"automated":[216],"assessment.":[218]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}