{"id":"https://openalex.org/W1651121916","doi":"https://doi.org/10.1109/rivf.2019.8713738","title":"Automated Change Detection and Reactive Clustering in Multivariate Streaming Data","display_name":"Automated Change Detection and Reactive Clustering in Multivariate Streaming Data","publication_year":2019,"publication_date":"2019-03-01","ids":{"openalex":"https://openalex.org/W1651121916","doi":"https://doi.org/10.1109/rivf.2019.8713738","mag":"1651121916"},"language":"en","primary_location":{"id":"doi:10.1109/rivf.2019.8713738","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rivf.2019.8713738","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE-RIVF International Conference on Computing and Communication Technologies (RIVF)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1311.0505","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002824473","display_name":"Dang-Hoan Tran","orcid":null},"institutions":[{"id":"https://openalex.org/I73685970","display_name":"Vietnam Maritime University","ror":"https://ror.org/03z9fzp04","country_code":"VN","type":"education","lineage":["https://openalex.org/I73685970"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Dang-Hoan Tran","raw_affiliation_strings":["Faculty of Information Technolog, Vietnam Maritime University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Technolog, Vietnam Maritime University","institution_ids":["https://openalex.org/I73685970"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5002824473"],"corresponding_institution_ids":["https://openalex.org/I73685970"],"apc_list":null,"apc_paid":null,"fwci":0.5639,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.7347224,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9965000152587891,"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":0.9965000152587891,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.991599977016449,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.98580002784729,"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/cluster-analysis","display_name":"Cluster analysis","score":0.851997435092926},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.7704359292984009},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7276618480682373},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6766701936721802},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.636594295501709},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6272156238555908},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5653116106987},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.4557059705257416},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.43820473551750183},{"id":"https://openalex.org/keywords/streaming-data","display_name":"Streaming data","score":0.42043113708496094},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37271857261657715},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.22797483205795288},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.21915727853775024},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.13669952750205994}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.851997435092926},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.7704359292984009},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7276618480682373},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6766701936721802},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.636594295501709},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6272156238555908},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5653116106987},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.4557059705257416},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.43820473551750183},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.42043113708496094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37271857261657715},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.22797483205795288},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.21915727853775024},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.13669952750205994},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/rivf.2019.8713738","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rivf.2019.8713738","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE-RIVF International Conference on Computing and Communication Technologies (RIVF)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1311.0505","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1311.0505","pdf_url":"https://arxiv.org/pdf/1311.0505","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:1651121916","is_oa":true,"landing_page_url":"https://arxiv.org/abs/1311.0505","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.765.4302","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.765.4302","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1311.0505.pdf","raw_type":"text"},{"id":"doi:10.48550/arxiv.1311.0505","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1311.0505","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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1311.0505","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1311.0505","pdf_url":"https://arxiv.org/pdf/1311.0505","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W1651121916.pdf"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W185701452","https://openalex.org/W1563234575","https://openalex.org/W1589063909","https://openalex.org/W1921457292","https://openalex.org/W2011430131","https://openalex.org/W2013893030","https://openalex.org/W2037193886","https://openalex.org/W2073459066","https://openalex.org/W2095897464","https://openalex.org/W2119516915","https://openalex.org/W2120016815","https://openalex.org/W2122951085","https://openalex.org/W2170936641","https://openalex.org/W4231029117","https://openalex.org/W6639988857","https://openalex.org/W6668990524","https://openalex.org/W6677987460","https://openalex.org/W6688325169"],"related_works":["https://openalex.org/W2962951775","https://openalex.org/W2941162567","https://openalex.org/W2758474378","https://openalex.org/W3040582905","https://openalex.org/W2361269346","https://openalex.org/W3111313451","https://openalex.org/W2075022587","https://openalex.org/W2806745815","https://openalex.org/W138386825","https://openalex.org/W2991307025","https://openalex.org/W3135180257","https://openalex.org/W3133728207","https://openalex.org/W3200506487","https://openalex.org/W2916228103","https://openalex.org/W3026928931","https://openalex.org/W2057287953","https://openalex.org/W2920690171","https://openalex.org/W2979783877","https://openalex.org/W1566520830","https://openalex.org/W2912343591"],"abstract_inverted_index":{"Many":[0],"automated":[1,19,96],"systems":[2],"need":[3],"the":[4,11,34,42,47,51,54,58,132,137,142],"capability":[5],"of":[6,80,134],"automatic":[7],"change":[8,20,72,86,101,119],"detection":[9,13,21,91,128],"without":[10],"given":[12],"threshold.":[14],"This":[15],"paper":[16],"presents":[17],"an":[18,95],"algorithm":[22,108],"in":[23,136],"streaming":[24,110,125],"multivariate":[25,124],"data.":[26,111,126],"Two":[27],"overlapping":[28],"windows":[29],"are":[30],"used":[31,40],"to":[32],"quantify":[33],"changes.":[35],"While":[36],"a":[37,71,78,105],"window":[38,44,56,143],"is":[39,49,76,94],"as":[41],"reference":[43,138],"from":[45],"which":[46],"clustering":[48,107],"created,":[50],"other":[52],"called":[53],"current":[55],"captures":[57],"newly":[59,64],"incoming":[60,65],"data":[61,66],"points.":[62],"A":[63],"point":[67,73],"can":[68],"be":[69],"considered":[70],"if":[74],"it":[75,93],"not":[77,89],"member":[79],"any":[81],"cluster.":[82],"As":[83],"our":[84,117],"clustering-based":[85,118],"detector":[87,120],"does":[88],"require":[90],"threshold,":[92],"detector.":[97],"Based":[98],"on":[99,131,141],"this":[100],"detector,":[102],"we":[103],"propose":[104],"reactive":[106],"for":[109],"Our":[112],"empirical":[113],"results":[114],"show":[115],"that":[116],"works":[121],"well":[122],"with":[123],"The":[127],"accuracy":[129],"depends":[130],"number":[133],"clusters":[135],"window,":[139],"and":[140],"width.":[144]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}