{"id":"https://openalex.org/W4399163438","doi":"https://doi.org/10.14778/3654621.3654627","title":"Outlier Summarization via Human Interpretable Rules","display_name":"Outlier Summarization via Human Interpretable Rules","publication_year":2024,"publication_date":"2024-03-01","ids":{"openalex":"https://openalex.org/W4399163438","doi":"https://doi.org/10.14778/3654621.3654627"},"language":"en","primary_location":{"id":"doi:10.14778/3654621.3654627","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3654621.3654627","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"Proceedings of the VLDB Endowment","raw_type":"journal-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/A5044971195","display_name":"Yuhao Deng","orcid":"https://orcid.org/0009-0002-4473-4527"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuhao Deng","raw_affiliation_strings":["Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102937215","display_name":"Yu Wang","orcid":"https://orcid.org/0000-0002-0294-8706"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I2803209242","display_name":"University of California System","ror":"https://ror.org/00pjdza24","country_code":"US","type":"education","lineage":["https://openalex.org/I2803209242"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Yu Wang","raw_affiliation_strings":["Beijing Institute of Technology","University of California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"University of California","institution_ids":["https://openalex.org/I2803209242"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049926126","display_name":"Lei Cao","orcid":"https://orcid.org/0000-0001-9909-8607"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lei Cao","raw_affiliation_strings":["University of Arizona/MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Arizona/MIT","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081418643","display_name":"Lianpeng Qiao","orcid":"https://orcid.org/0000-0002-5401-6222"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianpeng Qiao","raw_affiliation_strings":["Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100339104","display_name":"Yuping Wang","orcid":"https://orcid.org/0000-0001-6868-0004"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I2803209242","display_name":"University of California System","ror":"https://ror.org/00pjdza24","country_code":"US","type":"education","lineage":["https://openalex.org/I2803209242"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Yuping Wang","raw_affiliation_strings":["Beijing Institute of Technology","University of California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"University of California","institution_ids":["https://openalex.org/I2803209242"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085955819","display_name":"Jingzhe Xu","orcid":"https://orcid.org/0000-0002-5525-5153"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingzhe Xu","raw_affiliation_strings":["Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108577922","display_name":"Yizhou Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yizhou Yan","raw_affiliation_strings":["Worcester Polytechnic Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037742794","display_name":"Samuel Madden","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109586","display_name":"Moscow Institute of Thermal Technology","ror":"https://ror.org/021es5e59","country_code":"RU","type":"facility","lineage":["https://openalex.org/I4210109586"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Samuel Madden","raw_affiliation_strings":["MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT","institution_ids":["https://openalex.org/I4210109586"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5044971195"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":1.2588,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.82361965,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"17","issue":"7","first_page":"1591","last_page":"1604"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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":1.0,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9976999759674072,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9890000224113464,"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/outlier","display_name":"Outlier","score":0.784885048866272},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7842467427253723},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.775293231010437},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7414178848266602},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.6554559469223022},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6204129457473755},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5606499314308167},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5514168739318848},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5480754375457764},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.48777347803115845},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4334678053855896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4296558201313019},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10834315419197083}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.784885048866272},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7842467427253723},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.775293231010437},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7414178848266602},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.6554559469223022},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6204129457473755},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5606499314308167},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5514168739318848},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5480754375457764},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48777347803115845},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4334678053855896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4296558201313019},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10834315419197083},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14778/3654621.3654627","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3654621.3654627","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"Proceedings of the VLDB Endowment","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1530232915","https://openalex.org/W1673310716","https://openalex.org/W1787224781","https://openalex.org/W1966602182","https://openalex.org/W2047182010","https://openalex.org/W2091429054","https://openalex.org/W2103459159","https://openalex.org/W2107306718","https://openalex.org/W2125283600","https://openalex.org/W2151502664","https://openalex.org/W2153476503","https://openalex.org/W2161160262","https://openalex.org/W2282821441","https://openalex.org/W2296719434","https://openalex.org/W2316630624","https://openalex.org/W2367397349","https://openalex.org/W2402668406","https://openalex.org/W2606882704","https://openalex.org/W2612177096","https://openalex.org/W2613751718","https://openalex.org/W2762153450","https://openalex.org/W2775696413","https://openalex.org/W2788403449","https://openalex.org/W2883424428","https://openalex.org/W2911980033","https://openalex.org/W2962982021","https://openalex.org/W2971273612","https://openalex.org/W3030764521","https://openalex.org/W4210394794","https://openalex.org/W4236137412","https://openalex.org/W4253461361","https://openalex.org/W4254182148","https://openalex.org/W4256141317","https://openalex.org/W4293210185","https://openalex.org/W4372267129","https://openalex.org/W4381329328","https://openalex.org/W4383503590","https://openalex.org/W4396601766"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W2499612753","https://openalex.org/W1995723671","https://openalex.org/W2164647769","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729"],"abstract_inverted_index":{"Outlier":[0],"detection":[1,23,85,210],"is":[2,133],"crucial":[3],"for":[4,114,184,215],"preventing":[5],"financial":[6],"fraud,":[7],"network":[8],"intrusions,":[9],"and":[10,20,29,77,82,95,132,177,219],"device":[11],"failures.":[12],"Users":[13],"often":[14],"expect":[15],"systems":[16],"to":[17,25,39,80,104,143,155,206,217],"automatically":[18],"summarize":[19,81,156,207],"interpret":[21],"outlier":[22,84,192,209],"results":[24,86],"reduce":[26],"human":[27],"effort":[28],"convert":[30],"outliers":[31,58],"into":[32,171],"actionable":[33],"insights.":[34],"However,":[35],"existing":[36],"methods":[37],"fail":[38],"effectively":[40,144],"assist":[41],"users":[42],"in":[43,59,135,139],"identifying":[44],"the":[45,60,129,200,203,208],"root":[46],"causes":[47],"of":[48,109,120,181,202],"outliers,":[49],"as":[50],"they":[51],"only":[52],"pinpoint":[53],"data":[54,150,169,176],"attributes":[55,94],"without":[56],"considering":[57],"same":[61],"subspace":[62],"may":[63],"have":[64],"different":[65],"causes.":[66],"To":[67],"fill":[68],"this":[69,137],"gap,":[70],"we":[71,160],"propose":[72,161],"STAIR,":[73],"which":[74],"learns":[75,178],"concise":[76],"human-understandable":[78],"rules":[79,91,110,131,183,204],"explain":[83],"with":[87,111,157],"finer":[88],"granularity.":[89],"These":[90],"consider":[92],"both":[93],"associated":[96],"values.":[97],"STAIR":[98,121,164,197],"employs":[99],"an":[100],"interpretation-aware":[101],"optimization":[102],"objective":[103,138],"generate":[105],"a":[106,123,162,179],"small":[107],"number":[108],"minimal":[112],"complexity":[113,201],"strong":[115],"interpretability.":[116],"The":[117],"learning":[118],"algorithm":[119],"produces":[122],"rule":[124],"set":[125,180],"by":[126],"iteratively":[127],"splitting":[128],"large":[130],"optimal":[134],"maximizing":[136],"each":[140,185],"iteration.":[141],"Moreover,":[142],"handle":[145],"high":[146],"dimensional,":[147],"highly":[148],"complex":[149],"sets":[151],"that":[152,196],"are":[153],"hard":[154],"simple":[158],"rules,":[159],"localized":[163,182],"approach,":[165],"called":[166],"L-STAIR.":[167],"Taking":[168],"locality":[170],"consideration,":[172],"it":[173],"simultaneously":[174],"partitions":[175],"partition.":[186],"Our":[187],"experimental":[188],"study":[189],"on":[190],"many":[191],"benchmark":[193],"datasets":[194],"shows":[195],"significantly":[198],"reduces":[199],"required":[205],"results,":[211],"thus":[212],"more":[213],"amenable":[214],"humans":[216],"understand":[218],"evaluate.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}