{"id":"https://openalex.org/W2797507767","doi":"https://doi.org/10.1145/3297280.3297329","title":"Graph-based selective outlier ensembles","display_name":"Graph-based selective outlier ensembles","publication_year":2019,"publication_date":"2019-04-08","ids":{"openalex":"https://openalex.org/W2797507767","doi":"https://doi.org/10.1145/3297280.3297329","mag":"2797507767"},"language":"en","primary_location":{"id":"doi:10.1145/3297280.3297329","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3297280.3297329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1804.06378","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017625171","display_name":"Hamed Sarvari","orcid":null},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hamed Sarvari","raw_affiliation_strings":["George Mason University","#N#George Mason University#N#"],"affiliations":[{"raw_affiliation_string":"George Mason University","institution_ids":["https://openalex.org/I162714631"]},{"raw_affiliation_string":"#N#George Mason University#N#","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090148962","display_name":"Carlotta Domeniconi","orcid":"https://orcid.org/0000-0003-2140-9596"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carlotta Domeniconi","raw_affiliation_strings":["George Mason University","#N#George Mason University#N#"],"affiliations":[{"raw_affiliation_string":"George Mason University","institution_ids":["https://openalex.org/I162714631"]},{"raw_affiliation_string":"#N#George Mason University#N#","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036321638","display_name":"Giovanni Stilo","orcid":"https://orcid.org/0000-0002-2092-0213"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giovanni Stilo","raw_affiliation_strings":["Sapienza Universit\u00e0 di Roma, Rome, Italy","Sapienza\u2013Universit\u00e0 di Roma, Rome, Italy"],"affiliations":[{"raw_affiliation_string":"Sapienza Universit\u00e0 di Roma, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]},{"raw_affiliation_string":"Sapienza\u2013Universit\u00e0 di Roma, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5017625171"],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00442994,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"518","last_page":"525"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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":0.9997000098228455,"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/T11220","display_name":"Water Systems and Optimization","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12391","display_name":"Artificial Immune Systems Applications","score":0.9531000256538391,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.696017861366272},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6761351823806763},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5807953476905823},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5771150588989258},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5208373665809631},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4880334436893463},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4814971685409546},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.4674307703971863},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.42801928520202637},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4117942154407501},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29894787073135376}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.696017861366272},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6761351823806763},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5807953476905823},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5771150588989258},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5208373665809631},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4880334436893463},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4814971685409546},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.4674307703971863},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.42801928520202637},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4117942154407501},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29894787073135376}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3297280.3297329","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3297280.3297329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1804.06378","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1804.06378","pdf_url":"https://arxiv.org/pdf/1804.06378","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":"","raw_type":"text"},{"id":"mag:2797507767","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1804.06378.pdf","pdf_url":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1804.06378","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1804.06378","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1804.06378","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1804.06378","pdf_url":"https://arxiv.org/pdf/1804.06378","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":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2797507767.pdf","grobid_xml":"https://content.openalex.org/works/W2797507767.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W164607750","https://openalex.org/W201238001","https://openalex.org/W1707848225","https://openalex.org/W1853854734","https://openalex.org/W1966716734","https://openalex.org/W1967761844","https://openalex.org/W1969650088","https://openalex.org/W1990106316","https://openalex.org/W2041184937","https://openalex.org/W2050439513","https://openalex.org/W2056081083","https://openalex.org/W2070333970","https://openalex.org/W2082938293","https://openalex.org/W2097645701","https://openalex.org/W2097714558","https://openalex.org/W2101549186","https://openalex.org/W2102999520","https://openalex.org/W2110784166","https://openalex.org/W2124536999","https://openalex.org/W2129281431","https://openalex.org/W2144182447","https://openalex.org/W2144419338","https://openalex.org/W2146511318","https://openalex.org/W2150593711","https://openalex.org/W2160868604","https://openalex.org/W2182722412","https://openalex.org/W2242345359","https://openalex.org/W2249382963","https://openalex.org/W2282861635","https://openalex.org/W2285831592","https://openalex.org/W2296719434","https://openalex.org/W2406556692","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W2999008901","https://openalex.org/W4253461361"],"related_works":["https://openalex.org/W2271466582","https://openalex.org/W3137655554","https://openalex.org/W3082790776","https://openalex.org/W2528633616","https://openalex.org/W2116984363","https://openalex.org/W2097645701","https://openalex.org/W2403905234","https://openalex.org/W2530206022","https://openalex.org/W3154936041","https://openalex.org/W2002767255","https://openalex.org/W2031574473","https://openalex.org/W2036987424","https://openalex.org/W2947716341","https://openalex.org/W2025395689","https://openalex.org/W2309276681","https://openalex.org/W7842670","https://openalex.org/W2072562818","https://openalex.org/W2888166649","https://openalex.org/W2294042063","https://openalex.org/W2946058483"],"abstract_inverted_index":{"An":[0,184],"ensemble":[1,94,175,208],"technique":[2],"is":[3,26,43,131],"characterized":[4,132],"by":[5,13,133],"the":[6,10,14,24,35,52,55,67,81,85,88,91,99,104,139,148,163,171],"mechanism":[7,15],"that":[8,16,44,201],"generates":[9],"components":[11,46,82,176],"and":[12,73,145,195],"combines":[17],"them.":[18],"A":[19,38,126],"common":[20],"way":[21],"to":[22,27,31,49,69,84,151],"achieve":[23],"consensus":[25,56],"enable":[28],"each":[29],"component":[30],"equally":[32],"participate":[33],"in":[34,66,128,181],"aggregation":[36],"process.":[37],"problem":[39,106,172,180],"with":[40],"this":[41,60,114,129],"approach":[42,203],"poor":[45],"are":[47,98],"likely":[48],"negatively":[50],"affect":[51],"quality":[53],"of":[54,80,87,93,122,155,162,173,192],"result.":[57],"To":[58],"address":[59],"issue,":[61],"alternatives":[62],"have":[63],"been":[64,111],"explored":[65],"literature":[68],"build":[70],"selective":[71,206],"classifier":[72],"cluster":[74],"ensembles,":[75],"where":[76],"only":[77],"a":[78,118,142,153,159,178,182,190],"subset":[79,154],"contributes":[83],"computation":[86],"consensus.":[89],"Of":[90],"family":[92],"methods,":[95],"outlier":[96,108,207],"ensembles":[97,109],"least":[100],"studied.":[101],"Only":[102],"recently,":[103],"selection":[105,124,166],"for":[107],"has":[110],"discussed.":[112],"In":[113],"work":[115],"we":[116,169],"define":[117,158],"new":[119],"graph-based":[120,164],"class":[121,130],"ranking":[123,165],"methods.":[125,196],"method":[127],"two":[134],"main":[135],"steps:":[136],"(1)":[137],"Mapping":[138],"rankings":[140],"onto":[141,177],"graph":[143,150],"structure;":[144],"(2)":[146],"Mining":[147],"resulting":[149],"identify":[152],"rankings.":[156],"We":[157],"specific":[160],"instance":[161],"class.":[167],"Specifically,":[168],"map":[170],"selecting":[174],"mining":[179],"graph.":[183],"extensive":[185],"evaluation":[186],"was":[187],"conducted":[188],"on":[189],"variety":[191],"heterogeneous":[193],"data":[194],"Our":[197],"empirical":[198],"results":[199],"show":[200],"our":[202],"outperforms":[204],"state-of-the-art":[205],"techniques.":[209]},"counts_by_year":[],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}