{"id":"https://openalex.org/W3168527239","doi":"https://doi.org/10.1145/3442381.3449868","title":"Beyond Outlier Detection: Outlier Interpretation by Attention-Guided Triplet Deviation Network","display_name":"Beyond Outlier Detection: Outlier Interpretation by Attention-Guided Triplet Deviation Network","publication_year":2021,"publication_date":"2021-04-19","ids":{"openalex":"https://openalex.org/W3168527239","doi":"https://doi.org/10.1145/3442381.3449868","mag":"3168527239"},"language":"en","primary_location":{"id":"doi:10.1145/3442381.3449868","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449868","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3442381.3449868","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091676049","display_name":"Hongzuo Xu","orcid":"https://orcid.org/0000-0001-8074-1244"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongzuo Xu","raw_affiliation_strings":["National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100429826","display_name":"Yijie Wang","orcid":"https://orcid.org/0000-0002-2913-4016"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yijie Wang","raw_affiliation_strings":["National University of Defence Technology, China","National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"National University of Defence Technology, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000084858","display_name":"Songlei Jian","orcid":"https://orcid.org/0000-0002-1435-0410"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songlei Jian","raw_affiliation_strings":["National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076716112","display_name":"Zhenyu Huang","orcid":"https://orcid.org/0000-0003-4161-9427"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Huang","raw_affiliation_strings":["National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100424209","display_name":"Yongjun Wang","orcid":"https://orcid.org/0000-0002-3627-1465"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongjun Wang","raw_affiliation_strings":["National University of Defence Technology, China","National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"National University of Defence Technology, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432409","display_name":"Ning Liu","orcid":"https://orcid.org/0000-0002-8966-7869"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Liu","raw_affiliation_strings":["National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100325874","display_name":"Fei Li","orcid":"https://orcid.org/0000-0003-0332-4011"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Li","raw_affiliation_strings":["Alibaba Cloud Computing Co. Ltd., China"],"affiliations":[{"raw_affiliation_string":"Alibaba Cloud Computing Co. Ltd., China","institution_ids":["https://openalex.org/I45928872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5091676049"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":3.9431,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.94605181,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1328","last_page":"1339"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9873999953269958,"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":0.9761999845504761,"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":0.822364091873169},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.8085756301879883},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.686553955078125},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6154980063438416},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.508101224899292},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49881458282470703},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48328807950019836},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.48293086886405945},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.43699532747268677},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4200628399848938},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2330184280872345}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.822364091873169},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8085756301879883},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.686553955078125},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6154980063438416},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.508101224899292},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49881458282470703},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48328807950019836},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.48293086886405945},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.43699532747268677},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4200628399848938},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2330184280872345},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3442381.3449868","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449868","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3442381.3449868","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449868","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W112228497","https://openalex.org/W1966836840","https://openalex.org/W1995443851","https://openalex.org/W1999518899","https://openalex.org/W2067092965","https://openalex.org/W2091429054","https://openalex.org/W2282821441","https://openalex.org/W2316630624","https://openalex.org/W2336788611","https://openalex.org/W2338990760","https://openalex.org/W2564534161","https://openalex.org/W2618851150","https://openalex.org/W2735992466","https://openalex.org/W2774228929","https://openalex.org/W2804236575","https://openalex.org/W2807955733","https://openalex.org/W2811024573","https://openalex.org/W2896488239","https://openalex.org/W2905191756","https://openalex.org/W2910965336","https://openalex.org/W2949848919","https://openalex.org/W2962819609","https://openalex.org/W2963338867","https://openalex.org/W2964308564","https://openalex.org/W2985323229","https://openalex.org/W2999242702","https://openalex.org/W3004149215","https://openalex.org/W3007108802","https://openalex.org/W3023354380","https://openalex.org/W3097094324","https://openalex.org/W3099206234","https://openalex.org/W3128452405","https://openalex.org/W3128465814","https://openalex.org/W3135550350","https://openalex.org/W4245050711"],"related_works":["https://openalex.org/W3100286349","https://openalex.org/W2896134808","https://openalex.org/W4289378085","https://openalex.org/W4294291164","https://openalex.org/W3172436493","https://openalex.org/W2499612753","https://openalex.org/W1887135636","https://openalex.org/W1995723671","https://openalex.org/W4287164812","https://openalex.org/W2386063599"],"abstract_inverted_index":{"Outlier":[0,117],"detection":[1],"is":[2,10,25,242],"an":[3,128,180,229],"important":[4],"task":[5],"in":[6,13,79,102],"many":[7],"domains":[8],"and":[9,39,94,131,163,189,192,216,248,263,271],"intensively":[11],"studied":[12],"the":[14,53,59,77,84,143,149,152,197,213,217,221,246],"past":[15],"decade.":[16],"Further,":[17],"how":[18,133],"to":[19,35,83,90,134,137,148,244],"explain":[20],"outliers,":[21],"i.e.,":[22],"outlier":[23,71,78,199,235],"interpretation,":[24],"more":[26],"significant,":[27],"which":[28,169],"can":[29,200,225],"provide":[30],"valuable":[31],"insights":[32],"for":[33,116],"analysts":[34],"better":[36,202],"understand,":[37],"solve,":[38],"prevent":[40],"these":[41],"detected":[42],"outliers.":[43],"However,":[44],"only":[45],"limited":[46],"studies":[47],"consider":[48],"this":[49,107],"problem.":[50],"Most":[51],"of":[52,76,121,145,151,158,196,209,232,240,250],"existing":[54],"methods":[55],"are":[56,170],"based":[57],"on":[58,259],"score-and-search":[60],"manner.":[61],"They":[62],"select":[63],"a":[64,96,110,123,159,164,173,207],"feature":[65,160],"subspace":[66,98,208],"as":[67,228],"interpretation":[68,104],"per":[69],"queried":[70,153,198],"by":[72,172],"estimating":[73],"outlying":[74,194],"scores":[75],"searched":[80],"subspaces.":[81],"Due":[82],"tremendous":[85],"searching":[86,122],"space,":[87],"they":[88],"have":[89],"utilize":[91],"pruning":[92],"strategies":[93],"set":[95],"maximum":[97],"length,":[99],"often":[100],"resulting":[101],"suboptimal":[103],"results.":[105],"Accordingly,":[106],"paper":[108],"proposes":[109],"novel":[111],"Attention-guided":[112],"Triplet":[113],"deviation":[114],"network":[115],"interpretatioN":[118],"(ATON).":[119],"Instead":[120],"subspace,":[124],"ATON":[125,156,204,224,254],"directly":[126],"learns":[127,132],"embedding":[129,139,161,183,214],"space":[130,184],"attach":[135],"attention":[136,218],"each":[138,146],"dimension":[140,147],"(i.e.,":[141],"capturing":[142],"contribution":[144],"outlierness":[150],"outlier).":[154],"Specifically,":[155],"consists":[157],"module":[162,215],"customized":[165],"self-attention":[166],"learning":[167],"module,":[168],"optimized":[171],"triplet":[174],"deviation-based":[175],"loss":[176],"function.":[177],"We":[178],"obtain":[179],"optimal":[181],"attention-guided":[182],"with":[185],"expanded":[186],"high-level":[187],"information":[188],"rich":[190],"semantics,":[191],"thus":[193],"behaviors":[195],"be":[201,226],"unfolded.":[203],"finally":[205],"distills":[206],"original":[210],"features":[211],"from":[212],"coefficient.":[219],"With":[220],"good":[222,265],"generality,":[223],"employed":[227],"additional":[230],"step":[231],"any":[233],"black-box":[234],"detector.":[236],"A":[237],"comprehensive":[238],"suite":[239],"experiments":[241],"conducted":[243],"evaluate":[245],"effectiveness":[247],"efficiency":[249],"ATON.":[251],"The":[252],"proposed":[253],"significantly":[255],"outperforms":[256],"state-of-the-art":[257],"competitors":[258],"12":[260],"real-world":[261],"datasets":[262],"obtains":[264],"scalability":[266],"w.r.t.":[267],"both":[268],"data":[269,272],"dimensionality":[270],"size.":[273]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
