{"id":"https://openalex.org/W2011396747","doi":"https://doi.org/10.1145/2020408.2020555","title":"An effective evaluation measure for clustering on evolving data streams","display_name":"An effective evaluation measure for clustering on evolving data streams","publication_year":2011,"publication_date":"2011-08-21","ids":{"openalex":"https://openalex.org/W2011396747","doi":"https://doi.org/10.1145/2020408.2020555","mag":"2011396747"},"language":"en","primary_location":{"id":"doi:10.1145/2020408.2020555","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2020408.2020555","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5022706154","display_name":"Hardy Kremer","orcid":null},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Hardy Kremer","raw_affiliation_strings":["RWTH Aachen University, Aachen, Germany","RWTH-Aachen University, Aachen, Germany"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I887968799"]},{"raw_affiliation_string":"RWTH-Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113641260","display_name":"Philipp Kranen","orcid":null},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Philipp Kranen","raw_affiliation_strings":["RWTH Aachen University, Aachen, Germany","RWTH-Aachen University, Aachen, Germany"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I887968799"]},{"raw_affiliation_string":"RWTH-Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085349943","display_name":"Timm Jansen","orcid":null},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Timm Jansen","raw_affiliation_strings":["RWTH Aachen University, Aachen, Germany","RWTH-Aachen University, Aachen, Germany"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I887968799"]},{"raw_affiliation_string":"RWTH-Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003335849","display_name":"Thomas Seidl","orcid":"https://orcid.org/0000-0002-4861-1412"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Seidl","raw_affiliation_strings":["RWTH Aachen University, Hamilton, Germany"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University, Hamilton, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080970505","display_name":"Albert Bifet","orcid":"https://orcid.org/0000-0002-8339-7773"},"institutions":[{"id":"https://openalex.org/I52179390","display_name":"University of Waikato","ror":"https://ror.org/013fsnh78","country_code":"NZ","type":"education","lineage":["https://openalex.org/I52179390"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Albert Bifet","raw_affiliation_strings":["University of Waikato Hamilton, Hamilton, New Zealand","University of Waikato Hamilton, Hamilton, New Zealand#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Waikato Hamilton, Hamilton, New Zealand","institution_ids":["https://openalex.org/I52179390"]},{"raw_affiliation_string":"University of Waikato Hamilton, Hamilton, New Zealand#TAB#","institution_ids":["https://openalex.org/I52179390"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063502807","display_name":"Geoffrey Holmes","orcid":"https://orcid.org/0000-0003-0433-8925"},"institutions":[{"id":"https://openalex.org/I52179390","display_name":"University of Waikato","ror":"https://ror.org/013fsnh78","country_code":"NZ","type":"education","lineage":["https://openalex.org/I52179390"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Geoff Holmes","raw_affiliation_strings":["University of Waikato Hamilton, Hamilton, New Zealand","University of Waikato Hamilton, Hamilton, New Zealand#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Waikato Hamilton, Hamilton, New Zealand","institution_ids":["https://openalex.org/I52179390"]},{"raw_affiliation_string":"University of Waikato Hamilton, Hamilton, New Zealand#TAB#","institution_ids":["https://openalex.org/I52179390"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087785022","display_name":"Bernhard Pfahringer","orcid":"https://orcid.org/0000-0002-3732-5787"},"institutions":[{"id":"https://openalex.org/I52179390","display_name":"University of Waikato","ror":"https://ror.org/013fsnh78","country_code":"NZ","type":"education","lineage":["https://openalex.org/I52179390"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Bernhard Pfahringer","raw_affiliation_strings":["University of Waikato Hamilton, Hamilton, New Zealand","University of Waikato Hamilton, Hamilton, New Zealand#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Waikato Hamilton, Hamilton, New Zealand","institution_ids":["https://openalex.org/I52179390"]},{"raw_affiliation_string":"University of Waikato Hamilton, Hamilton, New Zealand#TAB#","institution_ids":["https://openalex.org/I52179390"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5022706154"],"corresponding_institution_ids":["https://openalex.org/I887968799"],"apc_list":null,"apc_paid":null,"fwci":9.21,"has_fulltext":false,"cited_by_count":98,"citation_normalized_percentile":{"value":0.97788424,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"868","last_page":"876"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9990000128746033,"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":0.9990000128746033,"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":0.9957000017166138,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.986299991607666,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.8579784631729126},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8098393678665161},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.7712984085083008},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7439966201782227},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.7102610468864441},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5839778780937195},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.5542645454406738},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5445017218589783},{"id":"https://openalex.org/keywords/streams","display_name":"STREAMS","score":0.46175312995910645},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.44863361120224},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.4223436117172241},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.310712993144989},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29859960079193115},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.2742162346839905}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8579784631729126},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8098393678665161},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.7712984085083008},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7439966201782227},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.7102610468864441},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5839778780937195},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.5542645454406738},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5445017218589783},{"id":"https://openalex.org/C42090638","wikidata":"https://www.wikidata.org/wiki/Q4048907","display_name":"STREAMS","level":2,"score":0.46175312995910645},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.44863361120224},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.4223436117172241},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.310712993144989},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29859960079193115},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.2742162346839905},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2020408.2020555","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2020408.2020555","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:publications.rwth-aachen.de:125266","is_oa":false,"landing_page_url":"https://publications.rwth-aachen.de/record/125266","pdf_url":null,"source":{"id":"https://openalex.org/S4306401362","display_name":"RWTH Publications (RWTH Aachen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887968799","host_organization_name":"RWTH Aachen University","host_organization_lineage":["https://openalex.org/I887968799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining : August 21 - 24, 2011, San Diego, California, USA / sponsored by: ACM SIGKDD and ACM SIGMOD<br/>17. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, 2011-08-21 - 2011-08-24","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W182707955","https://openalex.org/W1493454437","https://openalex.org/W1520723760","https://openalex.org/W1527309986","https://openalex.org/W1560329957","https://openalex.org/W1606594487","https://openalex.org/W1949687736","https://openalex.org/W1971784203","https://openalex.org/W1992419399","https://openalex.org/W1999646319","https://openalex.org/W2002229540","https://openalex.org/W2008788779","https://openalex.org/W2016159616","https://openalex.org/W2029064186","https://openalex.org/W2030644393","https://openalex.org/W2033403400","https://openalex.org/W2049814849","https://openalex.org/W2060979493","https://openalex.org/W2065354671","https://openalex.org/W2087962968","https://openalex.org/W2088879945","https://openalex.org/W2092335550","https://openalex.org/W2108354365","https://openalex.org/W2113586398","https://openalex.org/W2117059686","https://openalex.org/W2119387804","https://openalex.org/W2122868074","https://openalex.org/W2126611302","https://openalex.org/W2129630294","https://openalex.org/W2131456395","https://openalex.org/W2135335717","https://openalex.org/W2138615112","https://openalex.org/W2140190241","https://openalex.org/W2141729166","https://openalex.org/W2144344912","https://openalex.org/W2145898068","https://openalex.org/W2152144380","https://openalex.org/W2160558030","https://openalex.org/W2170936641","https://openalex.org/W2319660501","https://openalex.org/W2478708596","https://openalex.org/W2913066018","https://openalex.org/W4235169531","https://openalex.org/W4252521233","https://openalex.org/W6616672150","https://openalex.org/W6650841088","https://openalex.org/W6680704940","https://openalex.org/W6698813454","https://openalex.org/W6770641979"],"related_works":["https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W2183916789","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2743735673","https://openalex.org/W2522231769","https://openalex.org/W4312214159","https://openalex.org/W2045938006","https://openalex.org/W2079625735"],"abstract_inverted_index":{"Due":[0],"to":[1,43,63,73,78],"the":[2,29,74,79,83,112],"ever":[3],"growing":[4],"presence":[5],"of":[6,15,31,108,115],"data":[7,35,84,117,130],"streams,":[8,36],"there":[9],"has":[10,40],"been":[11,25,41],"a":[12,91,134],"considerable":[13],"amount":[14],"research":[16],"on":[17,33,126],"stream":[18,96,138],"mining":[19],"algorithms.":[20],"While":[21],"many":[22],"algorithms":[23],"have":[24],"introduced":[26],"that":[27,131],"tackle":[28],"problem":[30],"clustering":[32,97,139],"evolving":[34,116],"hardly":[37],"any":[38],"attention":[39],"paid":[42],"appropriate":[44],"evaluation":[45,93],"measures.":[46],"Measures":[47],"developed":[48],"for":[49,95,137],"static":[50],"scenarios,":[51],"namely":[52],"structural":[53],"measures":[54],"and":[55,128],"ground-truth-based":[56],"measures,":[57],"cannot":[58],"correctly":[59],"reflect":[60],"errors":[61,109],"attributable":[62],"emerging,":[64],"splitting,":[65],"or":[66],"moving":[67],"clusters.":[68],"These":[69],"situations":[70],"are":[71],"inherent":[72],"streaming":[75],"context":[76],"due":[77],"dynamic":[80],"changes":[81],"in":[82,123],"distribution.":[85],"In":[86],"this":[87],"paper":[88],"we":[89],"develop":[90],"novel":[92],"measure":[94,136],"called":[98],"Cluster":[99],"Mapping":[100],"Measure":[101],"(CMM).":[102],"CMM":[103,132],"effectively":[104],"indicates":[105],"different":[106],"types":[107],"by":[110],"taking":[111],"important":[113],"properties":[114],"streams":[118],"into":[119],"account.":[120],"We":[121],"show":[122],"extensive":[124],"experiments":[125],"real":[127],"synthetic":[129],"is":[133],"robust":[135],"evaluation.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":10},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":7}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}