{"id":"https://openalex.org/W7136341698","doi":"https://doi.org/10.48550/arxiv.2603.12847","title":"Hierarchical Reference Sets for Robust Unsupervised Detection of Scattered and Clustered Outliers","display_name":"Hierarchical Reference Sets for Robust Unsupervised Detection of Scattered and Clustered Outliers","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7136341698","doi":"https://doi.org/10.48550/arxiv.2603.12847"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.12847","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12847","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.12847","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129430105","display_name":"Yiqun Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Yiqun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019987799","display_name":"Zexi Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Zexi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110436840","display_name":"Xiaopeng Luo","orcid":"https://orcid.org/0009-0005-9214-7716"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Xiaopeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129542382","display_name":"Yunlin Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yunlin","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5129430105"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9915000200271606,"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":0.9915000200271606,"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/T12127","display_name":"Software System Performance and Reliability","score":0.002300000051036477,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.0010000000474974513,"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/outlier","display_name":"Outlier","score":0.7703999876976013},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7572000026702881},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6776000261306763},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5878000259399414},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.4399999976158142},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4375999867916107},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.37529999017715454}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7703999876976013},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7572000026702881},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6776000261306763},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6658999919891357},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5878000259399414},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5095999836921692},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4823000133037567},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.4399999976158142},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4375999867916107},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.37529999017715454},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.3366999924182892},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.32600000500679016},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3034999966621399},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C169029474","wikidata":"https://www.wikidata.org/wiki/Q387942","display_name":"Local outlier factor","level":3,"score":0.2912999987602234}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.12847","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12847","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":"doi:10.48550/arxiv.2603.12847","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12847","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.5507053136825562,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Most":[0],"real-world":[1],"IoT":[2,37],"data":[3],"analysis":[4],"tasks,":[5,172],"such":[6,32],"as":[7,33],"clustering":[8,171],"and":[9,15,93,127,155,173],"anomaly":[10,118],"event":[11],"detection,":[12],"are":[13],"unsupervised":[14],"highly":[16],"susceptible":[17],"to":[18,25,57],"the":[19,88,108,132,137,149,179,182],"presence":[20],"of":[21,80,90,140,175,181],"outliers.":[22,42],"In":[23],"addition":[24],"sporadic":[26],"scattered":[27,92,141],"outliers":[28,71,142],"caused":[29],"by":[30,120],"factors":[31],"faulty":[34],"sensor":[35],"readings,":[36],"systems":[38],"often":[39],"exhibit":[40],"clustered":[41,70,146,157],"These":[43,69],"occur":[44],"when":[45],"multiple":[46],"devices":[47],"or":[48,63],"nodes":[49],"produce":[50],"similar":[51],"anomalous":[52],"measurements,":[53],"for":[54,76],"instance,":[55],"owing":[56],"localized":[58],"interference,":[59],"emerging":[60],"security":[61],"threats,":[62],"regional":[64],"false":[65],"alarms,":[66],"forming":[67],"micro-clusters.":[68],"can":[72],"be":[73],"easily":[74],"mistaken":[75],"normal":[77],"behavior":[78],"because":[79],"their":[81],"relatively":[82],"high":[83],"local":[84,126],"density,":[85],"thereby":[86],"obscuring":[87],"detection":[89,104],"both":[91,125],"contextual":[94],"anomalies.":[95],"To":[96],"address":[97],"this,":[98],"we":[99],"propose":[100],"a":[101],"novel":[102],"outlier":[103,158],"paradigm":[105],"that":[106],"leverages":[107],"natural":[109],"neighboring":[110],"relationships":[111],"using":[112],"graph":[113,150],"structures.":[114],"This":[115],"facilitates":[116],"multi-perspective":[117],"evaluation":[119,174],"incorporating":[121],"reference":[122],"sets":[123],"at":[124,190],"global":[128],"scales":[129],"derived":[130],"from":[131,145],"graph.":[133],"Our":[134],"approach":[135],"enables":[136],"effective":[138],"recognition":[139],"without":[143],"interference":[144],"anomalies,":[147],"whereas":[148],"structure":[151],"simultaneously":[152],"helps":[153],"reflect":[154],"isolate":[156],"groups.":[159],"Extensive":[160],"experiments,":[161],"including":[162],"comparative":[163],"performance":[164],"analysis,":[165],"ablation":[166],"studies,":[167],"validation":[168],"on":[169],"downstream":[170],"hyperparameter":[176],"sensitivity,":[177],"demonstrate":[178],"efficacy":[180],"proposed":[183],"method.":[184],"The":[185],"source":[186],"code":[187],"is":[188],"available":[189],"https://github.com/gordonlok/DROD.":[191]},"counts_by_year":[],"updated_date":"2026-03-17T07:05:13.627479","created_date":"2026-03-17T00:00:00"}
