{"id":"https://openalex.org/W2996592004","doi":"https://doi.org/10.1145/3368926.3369667","title":"Fast Distance-based Outlier Detection in Data Streams based on Micro-clusters","display_name":"Fast Distance-based Outlier Detection in Data Streams based on Micro-clusters","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2996592004","doi":"https://doi.org/10.1145/3368926.3369667","mag":"2996592004"},"language":"en","primary_location":{"id":"doi:10.1145/3368926.3369667","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3368926.3369667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth International Symposium on Information and Communication Technology  - SoICT 2019","raw_type":"proceedings-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/A5014978361","display_name":"Luan Tran","orcid":"https://orcid.org/0000-0001-6847-3398"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Luan Tran","raw_affiliation_strings":["University of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065712592","display_name":"Liyue Fan","orcid":"https://orcid.org/0000-0002-3819-1098"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liyue Fan","raw_affiliation_strings":["University at Albany, SUNY, SUNY, New York, USA"],"affiliations":[{"raw_affiliation_string":"University at Albany, SUNY, SUNY, New York, USA","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012068017","display_name":"Cyrus Shahabi","orcid":"https://orcid.org/0000-0001-9118-0681"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cyrus Shahabi","raw_affiliation_strings":["University of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5014978361"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":0.5601,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.76075422,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"162","last_page":"169"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.989799976348877,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9839000105857849,"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/anomaly-detection","display_name":"Anomaly detection","score":0.8412843346595764},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7826842069625854},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.7649322748184204},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6967002153396606},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6944770812988281},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6645271182060242},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6611064672470093},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.4812202751636505},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4601934254169464},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.41251885890960693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34819740056991577},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3354078233242035},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32827264070510864},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12503060698509216}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8412843346595764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7826842069625854},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.7649322748184204},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6967002153396606},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6944770812988281},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6645271182060242},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6611064672470093},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.4812202751636505},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4601934254169464},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.41251885890960693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34819740056991577},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3354078233242035},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32827264070510864},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12503060698509216}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3368926.3369667","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3368926.3369667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth International Symposium on Information and Communication Technology  - SoICT 2019","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1552339598","https://openalex.org/W1575097427","https://openalex.org/W1586118362","https://openalex.org/W2000219982","https://openalex.org/W2060952812","https://openalex.org/W2100832675","https://openalex.org/W2116300222","https://openalex.org/W2152576712","https://openalex.org/W2153610999","https://openalex.org/W2548218624","https://openalex.org/W2970207504","https://openalex.org/W4237219250"],"related_works":["https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729","https://openalex.org/W2998615029","https://openalex.org/W3190734578","https://openalex.org/W1595351371","https://openalex.org/W3121032028","https://openalex.org/W91065195"],"abstract_inverted_index":{"Continuous":[0],"outlier":[1,40,65,95],"detection":[2,41,96],"in":[3,10,17,93,97,130],"data":[4,11,52,68,98],"streams":[5],"is":[6,61],"one":[7],"important":[8],"topic":[9],"mining.":[12],"It":[13],"has":[14],"many":[15,33],"applications":[16],"public":[18],"health,":[19],"network":[20],"intrusion":[21],"detection,":[22],"and":[23,47,55,72,84,108,119,132,157],"fraud":[24],"detection.":[25],"Over":[26],"the":[27,59,64,90,104,110,125,159],"last":[28],"two":[29],"decades":[30],"of":[31,67,106],"research,":[32],"studies":[34],"have":[35],"been":[36],"conducted":[37],"on":[38,117],"distance-based":[39,94],"algorithms":[42,87,127,138],"which":[43],"are":[44,128,139],"viable,":[45],"scalable,":[46],"parameter-free":[48],"approaches.":[49],"Because":[50],"streaming":[51],"points":[53,69],"arrive":[54],"expire":[56],"over":[57],"time,":[58],"challenge":[60],"to":[62,141,155],"monitor":[63],"status":[66],"with":[70],"time":[71,131],"space":[73,133],"efficiency.":[74,134],"In":[75],"this":[76],"study,":[77],"we":[78,122],"propose":[79],"three":[80],"algorithms:":[81],"O-MCOD,":[82],"U-MCOD,":[83],"M-MCOD.":[85],"These":[86],"improve":[88],"upon":[89],"state-of-the-art":[91],"algorithm":[92,162],"streams,":[99],"i.e.,":[100],"MCOD,":[101,146,156],"by":[102],"relaxing":[103],"constraints":[105],"micro-clusters":[107],"using":[109],"minimal":[111],"probing":[112],"principal.":[113],"With":[114],"extensive":[115],"experiments":[116],"synthetic":[118],"real-world":[120],"datasets,":[121],"show":[123],"that":[124],"proposed":[126,137],"superior":[129],"Specially,":[135],"our":[136],"1.5":[140],"95":[142],"times":[143],"faster":[144],"than":[145],"require":[147],"as":[148,150],"low":[149],"25%":[151],"peak":[152],"memory":[153],"compared":[154],"outperform":[158],"most":[160],"recent":[161],"NETS.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
