{"id":"https://openalex.org/W2895831816","doi":"https://doi.org/10.1109/access.2018.2877138","title":"Efficient Data Stream Clustering With Sliding Windows Based on Locality-Sensitive Hashing","display_name":"Efficient Data Stream Clustering With Sliding Windows Based on Locality-Sensitive Hashing","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2895831816","doi":"https://doi.org/10.1109/access.2018.2877138","mag":"2895831816"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2877138","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2877138","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2877138","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056714381","display_name":"Jonghem Youn","orcid":"https://orcid.org/0000-0002-5770-9032"},"institutions":[{"id":"https://openalex.org/I4210144002","display_name":"Medipost (South Korea)","ror":"https://ror.org/03vnxht79","country_code":"KR","type":"company","lineage":["https://openalex.org/I4210144002"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jonghem Youn","raw_affiliation_strings":["Voost Inc., Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-5770-9032","affiliations":[{"raw_affiliation_string":"Voost Inc., Seoul, South Korea","institution_ids":["https://openalex.org/I4210144002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077087855","display_name":"Junho Shim","orcid":"https://orcid.org/0000-0003-4315-4117"},"institutions":[{"id":"https://openalex.org/I31766871","display_name":"Sookmyung Women's University","ror":"https://ror.org/00vvvt117","country_code":"KR","type":"education","lineage":["https://openalex.org/I31766871"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junho Shim","raw_affiliation_strings":["Department of Computer Science, Sookmyung Women\u2019s University, Seoul, South Korea","Department of Computer Science, Sookmyung Women's University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Sookmyung Women\u2019s University, Seoul, South Korea","institution_ids":["https://openalex.org/I31766871"]},{"raw_affiliation_string":"Department of Computer Science, Sookmyung Women's University, Seoul, South Korea","institution_ids":["https://openalex.org/I31766871"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102802605","display_name":"Sang\u2010goo Lee","orcid":"https://orcid.org/0000-0002-0063-0083"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sang-Goo Lee","raw_affiliation_strings":["Department of Computer Science and Engineering, Seoul National University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Seoul National University, Seoul, South Korea","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5056714381"],"corresponding_institution_ids":["https://openalex.org/I4210144002"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.8776,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.9285769,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"6","issue":null,"first_page":"63757","last_page":"63776"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.996999979019165,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.996999979019165,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11478","display_name":"Caching and Content Delivery","score":0.992900013923645,"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/cluster-analysis","display_name":"Cluster analysis","score":0.809358537197113},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.8058992624282837},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8015497922897339},{"id":"https://openalex.org/keywords/locality-sensitive-hashing","display_name":"Locality-sensitive hashing","score":0.7502667903900146},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.7403661608695984},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.570790708065033},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5481855273246765},{"id":"https://openalex.org/keywords/nearest-neighbor-chain-algorithm","display_name":"Nearest-neighbor chain algorithm","score":0.5425444841384888},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.53275465965271},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.5245276093482971},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.4833388030529022},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.45536085963249207},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.433615118265152},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.4301527440547943},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.42376214265823364},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.41421884298324585},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.41350260376930237},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.37356579303741455},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.321340411901474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2018817663192749}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.809358537197113},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.8058992624282837},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8015497922897339},{"id":"https://openalex.org/C74270461","wikidata":"https://www.wikidata.org/wiki/Q1625299","display_name":"Locality-sensitive hashing","level":4,"score":0.7502667903900146},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.7403661608695984},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.570790708065033},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5481855273246765},{"id":"https://openalex.org/C102164700","wikidata":"https://www.wikidata.org/wiki/Q17162702","display_name":"Nearest-neighbor chain algorithm","level":5,"score":0.5425444841384888},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.53275465965271},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.5245276093482971},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.4833388030529022},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.45536085963249207},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.433615118265152},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.4301527440547943},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.42376214265823364},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.41421884298324585},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.41350260376930237},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.37356579303741455},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.321340411901474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2018817663192749},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2877138","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2877138","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1c988431b55d4bbe8d4133f6515e3b39","is_oa":true,"landing_page_url":"https://doaj.org/article/1c988431b55d4bbe8d4133f6515e3b39","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 63757-63776 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2877138","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2877138","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6666105419","display_name":null,"funder_award_id":"NRF-2016M3C4A7952587","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G754306106","display_name":null,"funder_award_id":"2017R1E1A1A03070004","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W147860157","https://openalex.org/W182707955","https://openalex.org/W855829896","https://openalex.org/W1522565396","https://openalex.org/W1552074189","https://openalex.org/W1673310716","https://openalex.org/W1949687736","https://openalex.org/W1956536100","https://openalex.org/W1965555277","https://openalex.org/W1975852288","https://openalex.org/W1977983731","https://openalex.org/W1992968767","https://openalex.org/W2004355640","https://openalex.org/W2004625705","https://openalex.org/W2045964207","https://openalex.org/W2048442462","https://openalex.org/W2049744118","https://openalex.org/W2055902670","https://openalex.org/W2065347048","https://openalex.org/W2073459066","https://openalex.org/W2086959852","https://openalex.org/W2088340225","https://openalex.org/W2092335550","https://openalex.org/W2095897464","https://openalex.org/W2099395665","https://openalex.org/W2100369465","https://openalex.org/W2101717554","https://openalex.org/W2103201239","https://openalex.org/W2112482089","https://openalex.org/W2123297508","https://openalex.org/W2124334351","https://openalex.org/W2124507579","https://openalex.org/W2125954346","https://openalex.org/W2127218421","https://openalex.org/W2135335717","https://openalex.org/W2150593711","https://openalex.org/W2162006472","https://openalex.org/W2165232124","https://openalex.org/W2170740664","https://openalex.org/W2170936641","https://openalex.org/W2170988853","https://openalex.org/W2264057010","https://openalex.org/W2343620495","https://openalex.org/W2468525308","https://openalex.org/W2470810834","https://openalex.org/W2475262020","https://openalex.org/W2517974350","https://openalex.org/W2526347192","https://openalex.org/W2559950244","https://openalex.org/W2598498736","https://openalex.org/W2963411648","https://openalex.org/W3003253354","https://openalex.org/W3120740533","https://openalex.org/W3172377255","https://openalex.org/W4231029117","https://openalex.org/W4242365185","https://openalex.org/W4295114475","https://openalex.org/W6606145560","https://openalex.org/W6637131181","https://openalex.org/W6641203231","https://openalex.org/W6668990524","https://openalex.org/W6678824329","https://openalex.org/W6678914141","https://openalex.org/W6680192438","https://openalex.org/W6685018829"],"related_works":["https://openalex.org/W3094967175","https://openalex.org/W2166822184","https://openalex.org/W50423144","https://openalex.org/W2754607325","https://openalex.org/W2045263322","https://openalex.org/W3096071782","https://openalex.org/W2902799860","https://openalex.org/W4289129280","https://openalex.org/W2901290148","https://openalex.org/W2895831816"],"abstract_inverted_index":{"Data":[0],"stream":[1,38],"clustering":[2,14,39,126,150],"over":[3,40],"sliding":[4,41,44,68,155],"windows":[5,42],"generates":[6],"clusters":[7,122],"as":[8,60],"the":[9,64,67,80,82,85,88,92,128],"window":[10,20,45,65,69],"moves.":[11],"However,":[12],"iterative":[13],"using":[15,43,66],"all":[16],"data":[17,37,152],"in":[18,24,139],"a":[19,61,76,109,117],"is":[21],"highly":[22],"inefficient":[23],"terms":[25],"of":[26,63,87],"memory":[27],"use":[28],"and":[29,47,55,136],"computational":[30],"load.":[31],"In":[32,72,104],"this":[33],"paper,":[34],"we":[35,106],"improve":[36,148],"aggregation":[46,70],"nearest":[48,93,101],"neighbor":[49,102],"search":[50],"techniques.":[51],"Our":[52],"algorithm":[53,83,145],"constructs":[54],"maintains":[56],"temporal":[57],"group":[58],"features":[59],"summary":[62,89,119],"technique.":[71],"order":[73,140],"to":[74,115,120,124,141],"maintain":[75],"constant":[77],"size":[78,86],"for":[79,99],"summary,":[81],"reduces":[84],"by":[90],"joining":[91],"neighbor.":[94],"We":[95,131],"exploit":[96],"locality-sensitive":[97],"hashing":[98],"rapid":[100],"searching.":[103],"addition,":[105],"also":[107],"suggest":[108],"re-clustering":[110],"policy":[111],"that":[112,143],"determines":[113],"whether":[114],"append":[116],"new":[118],"pre-existing":[121],"or":[123],"perform":[125],"on":[127,134,151],"whole":[129],"summary.":[130],"conduct":[132],"experiments":[133],"real-world":[135],"synthetic":[137],"datasets":[138],"demonstrate":[142],"our":[144],"can":[146],"significantly":[147],"continuous":[149],"streams":[153],"with":[154],"windows.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6}],"updated_date":"2026-05-08T15:41:06.802602","created_date":"2025-10-10T00:00:00"}
