{"id":"https://openalex.org/W4293192601","doi":"https://doi.org/10.1109/icsc52841.2022.00047","title":"DistAD: A Distributed Generic Anomaly Detection Framework over Large KGs","display_name":"DistAD: A Distributed Generic Anomaly Detection Framework over Large KGs","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4293192601","doi":"https://doi.org/10.1109/icsc52841.2022.00047"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsc52841.2022.00047","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://zenodo.org/records/7669258/files/DistAD-%20A%20Distributed%20Generic%20Anomaly%20Detection%20Framework%20over%20Large%20KGs.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023256605","display_name":"Farshad Bakhshandegan Moghaddam","orcid":null},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"funder","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Farshad Bakhshandegan Moghaddam","raw_affiliation_strings":["University of Bonn, Bonn, Germany"],"affiliations":[{"raw_affiliation_string":"University of Bonn, Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067133778","display_name":"Jens Lehmann","orcid":"https://orcid.org/0000-0001-9108-4278"},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"funder","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jens Lehmann","raw_affiliation_strings":["University of Bonn, Bonn, Germany"],"affiliations":[{"raw_affiliation_string":"University of Bonn, Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034642813","display_name":"Hajira Jabeen","orcid":"https://orcid.org/0000-0003-1476-2121"},"institutions":[{"id":"https://openalex.org/I4210101898","display_name":"GESIS - Leibniz-Institute for the Social Sciences","ror":"https://ror.org/018afyw53","country_code":"DE","type":"funder","lineage":["https://openalex.org/I315704651","https://openalex.org/I4210101898"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Hajira Jabeen","raw_affiliation_strings":["GESIS-Leibniz Institute for the Social Sciences, Cologne, Germany"],"affiliations":[{"raw_affiliation_string":"GESIS-Leibniz Institute for the Social Sciences, Cologne, Germany","institution_ids":["https://openalex.org/I4210101898"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.289,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":2,"citation_normalized_percentile":{"value":0.36015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":69,"max":75},"biblio":{"volume":null,"issue":null,"first_page":"243","last_page":"250"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9996,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9996,"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/T11719","display_name":"Data Quality and Management","score":0.9967,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.994,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/linked-data","display_name":"Linked Data","score":0.6409489},{"id":"https://openalex.org/keywords/predicate","display_name":"Predicate (mathematical logic)","score":0.51972485},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.49080643}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8337182},{"id":"https://openalex.org/C147497476","wikidata":"https://www.wikidata.org/wiki/Q54872","display_name":"RDF","level":3,"score":0.77747494},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.71984273},{"id":"https://openalex.org/C69075417","wikidata":"https://www.wikidata.org/wiki/Q515701","display_name":"Linked data","level":3,"score":0.6409489},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5779681},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.5226771},{"id":"https://openalex.org/C140146324","wikidata":"https://www.wikidata.org/wiki/Q1144319","display_name":"Predicate (mathematical logic)","level":2,"score":0.51972485},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.49906874},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.49905443},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.49080643},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.47836703},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.43611962},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3872499},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35661274},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.26310468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18651345},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsc52841.2022.00047","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://zenodo.org/record/7669258","pdf_url":"https://zenodo.org/records/7669258/files/DistAD-%20A%20Distributed%20Generic%20Anomaly%20Detection%20Framework%20over%20Large%20KGs.pdf","source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":["European Organization for Nuclear Research"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://zenodo.org/record/7669258","pdf_url":"https://zenodo.org/records/7669258/files/DistAD-%20A%20Distributed%20Generic%20Anomaly%20Detection%20Framework%20over%20Large%20KGs.pdf","source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":["European Organization for Nuclear Research"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":21,"referenced_works":["https://openalex.org/W102708294","https://openalex.org/W140982117","https://openalex.org/W1876766592","https://openalex.org/W2022166150","https://openalex.org/W2038880450","https://openalex.org/W2040975718","https://openalex.org/W2049058890","https://openalex.org/W2082938293","https://openalex.org/W2087159174","https://openalex.org/W2094728533","https://openalex.org/W2122646361","https://openalex.org/W2129104508","https://openalex.org/W2162006472","https://openalex.org/W2551079787","https://openalex.org/W262440584","https://openalex.org/W2764318100","https://openalex.org/W277886906","https://openalex.org/W2899400605","https://openalex.org/W2963323165","https://openalex.org/W3134744668","https://openalex.org/W4246528899"],"related_works":["https://openalex.org/W82112649","https://openalex.org/W3128827045","https://openalex.org/W2945730294","https://openalex.org/W2776293731","https://openalex.org/W2400121884","https://openalex.org/W2283287182","https://openalex.org/W2058923328","https://openalex.org/W2054214855","https://openalex.org/W199330785","https://openalex.org/W1485690712"],"abstract_inverted_index":{"The":[0,160,179],"last":[1],"decades":[2],"have":[3,47],"witnessed":[4],"significant":[5],"advancements":[6],"in":[7,16,28,35,80,107,206],"terms":[8],"of":[9,19,31,38,74,151],"data":[10,20,32,46,109,197],"generation,":[11],"management,":[12],"and":[13,22,40,56,63,86,126,155,167],"maintenance":[14],"especially":[15],"the":[17,95,108,143,171,187],"area":[18],"lakes,":[21],"heterogeneous":[23],"data.":[24],"This":[25],"has":[26],"resulted":[27],"vast":[29,149],"amounts":[30],"becoming":[33],"available":[34],"a":[36,123,139,148],"variety":[37],"forms":[39],"formats":[41],"including":[42],"RDF.":[43],"As":[44],"RDF":[45,134,196],"been":[48],"created":[49],"by":[50],"liberal":[51],"curation":[52],"methods":[53],"(e.g.":[54],"crowd-sourcing":[55],"automatic":[57],"extraction":[58],"tools":[59],"with":[60],"limited":[61],"restriction":[62],"cross-validation":[64],"on":[65,132,181],"input":[66],"data),":[67],"they":[68],"are":[69],"prone":[70],"to":[71,103,145,157,193,201],"various":[72],"kinds":[73],"errors":[75,91],"that":[76,186],"can":[77,111],"be":[78,112],"hidden":[79,204],"different":[81,152],"dimensions":[82],"(i.e.":[83],"subject,":[84],"predicate,":[85],"object":[87],"level).":[88],"Detecting":[89],"those":[90],"not":[92,190],"only":[93,191],"improves":[94],"KGs":[96],"quality":[97],"but":[98,198],"also":[99,199],"makes":[100],"it":[101],"possible":[102],"detect":[104,158,203],"anomalous":[105],"events":[106],"which":[110],"used":[113],"for":[114,129,142],"subsequent":[115],"analysis.":[116],"In":[117],"this":[118],"paper,":[119],"we":[120],"present":[121],"DistAD,":[122],"generic,":[124],"scalable,":[125],"distributed":[127],"framework":[128,162,188],"anomaly":[130],"detection":[131],"large":[133],"knowledge":[135],"graphs.":[136],"DistAD":[137],"provides":[138],"great":[140],"granularity":[141],"end-users":[144],"select":[146],"from":[147],"number":[150],"algorithms,":[153],"methods,":[154],"(hyper-)parameters":[156],"outliers.":[159],"proposed":[161],"is":[163,189],"fully":[164,168],"open-source,":[165],"well-documented,":[166],"integrated":[169],"into":[170],"active":[172],"community":[173],"project":[174],"Semantic":[175],"Analytics":[176],"Stack":[177],"(SANSA).":[178],"experiments":[180],"real-world":[182],"use":[183],"cases":[184],"disclose":[185],"able":[192,200],"handle":[194],"huge":[195],"successfully":[202],"anomalies/outliers":[205],"KGs.":[207]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4293192601","counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2025-03-21T17:54:33.518946","created_date":"2022-08-27"}