{"id":"https://openalex.org/W1997728726","doi":"https://doi.org/10.1109/icde.2010.5447924","title":"Finding Clusters in subspaces of very large, multi-dimensional datasets","display_name":"Finding Clusters in subspaces of very large, multi-dimensional datasets","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W1997728726","doi":"https://doi.org/10.1109/icde.2010.5447924","mag":"1997728726"},"language":"en","primary_location":{"id":"doi:10.1109/icde.2010.5447924","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2010.5447924","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5085964688","display_name":"Robson L. F. Cordeiro","orcid":"https://orcid.org/0000-0002-6795-3004"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Robson L. F. Cordeiro","raw_affiliation_strings":["Computer Science Department, University of S\u00e3o Paulo, S\u00e3o Carlos, SP, Brazil","Computer Science Department - ICMC, University of S\u00e3o Paulo, 400 Trabalhador Saocarlense Ave, S\u00e3o Carlos 668, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of S\u00e3o Paulo, S\u00e3o Carlos, SP, Brazil","institution_ids":["https://openalex.org/I17974374"]},{"raw_affiliation_string":"Computer Science Department - ICMC, University of S\u00e3o Paulo, 400 Trabalhador Saocarlense Ave, S\u00e3o Carlos 668, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014783020","display_name":"Agma J. M. Traina","orcid":"https://orcid.org/0000-0003-4929-7258"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Agma J. M. Traina","raw_affiliation_strings":["Computer Science Department, University of S\u00e3o Paulo, S\u00e3o Carlos, SP, Brazil","Computer Science Department - ICMC, University of S\u00e3o Paulo, 400 Trabalhador Saocarlense Ave, S\u00e3o Carlos 668, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of S\u00e3o Paulo, S\u00e3o Carlos, SP, Brazil","institution_ids":["https://openalex.org/I17974374"]},{"raw_affiliation_string":"Computer Science Department - ICMC, University of S\u00e3o Paulo, 400 Trabalhador Saocarlense Ave, S\u00e3o Carlos 668, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035605036","display_name":"Christos Faloutsos","orcid":"https://orcid.org/0000-0003-2996-9790"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christos Faloutsos","raw_affiliation_strings":["School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA","School of Computer Science Carnegie Mellon University 5000 Forbes Ave, Pittsburgh PA 15213, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"School of Computer Science Carnegie Mellon University 5000 Forbes Ave, Pittsburgh PA 15213, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020611078","display_name":"Caetano Traina","orcid":"https://orcid.org/0000-0002-6625-6047"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Caetano Traina","raw_affiliation_strings":["Computer Science Department, University of S\u00e3o Paulo, S\u00e3o Carlos, SP, Brazil","Computer Science Department - ICMC, University of S\u00e3o Paulo, 400 Trabalhador Saocarlense Ave, S\u00e3o Carlos 668, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of S\u00e3o Paulo, S\u00e3o Carlos, SP, Brazil","institution_ids":["https://openalex.org/I17974374"]},{"raw_affiliation_string":"Computer Science Department - ICMC, University of S\u00e3o Paulo, 400 Trabalhador Saocarlense Ave, S\u00e3o Carlos 668, Brazil","institution_ids":["https://openalex.org/I17974374"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.9942,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.97364035,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"625","last_page":"636"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9959999918937683,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9959999918937683,"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/T12114","display_name":"Sensory Analysis and Statistical Methods","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13141","display_name":"Statistical Methods and Applications","score":0.9710999727249146,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.7758747339248657},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.7284214496612549},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6571053862571716},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5656799674034119},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5405939817428589},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5341106653213501},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.5117930769920349},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.47950226068496704},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4523591995239258},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.42002636194229126},{"id":"https://openalex.org/keywords/time-complexity","display_name":"Time complexity","score":0.4143984019756317},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27268093824386597},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2600911259651184},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08199051022529602}],"concepts":[{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.7758747339248657},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.7284214496612549},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6571053862571716},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5656799674034119},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5405939817428589},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5341106653213501},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.5117930769920349},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.47950226068496704},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4523591995239258},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.42002636194229126},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.4143984019756317},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27268093824386597},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2600911259651184},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08199051022529602},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icde.2010.5447924","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2010.5447924","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W107968503","https://openalex.org/W1566114229","https://openalex.org/W1672197616","https://openalex.org/W1977496278","https://openalex.org/W1988157641","https://openalex.org/W1995433152","https://openalex.org/W1998901634","https://openalex.org/W2049797265","https://openalex.org/W2065811242","https://openalex.org/W2073825221","https://openalex.org/W2079361215","https://openalex.org/W2089055054","https://openalex.org/W2093100781","https://openalex.org/W2099058255","https://openalex.org/W2103696938","https://openalex.org/W2118858274","https://openalex.org/W2126642639","https://openalex.org/W2153790277","https://openalex.org/W2161284614","https://openalex.org/W2161985854","https://openalex.org/W2472923625","https://openalex.org/W3003734944","https://openalex.org/W4234409091","https://openalex.org/W4237938455","https://openalex.org/W4253654031","https://openalex.org/W6633857196","https://openalex.org/W6683750689"],"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/W1887135636","https://openalex.org/W4287164812","https://openalex.org/W2386063599","https://openalex.org/W1975884855","https://openalex.org/W3213150849"],"abstract_inverted_index":{"We":[0,155],"propose":[1],"the":[2,22,66,122,182,194,218],"Multi-resolution":[3],"Correlation":[4],"Cluster":[5],"detection":[6],"(MrCC),":[7],"a":[8,45,69],"novel,":[9],"scalable":[10],"method":[11],"to":[12,17,27,116,137,164,171,225],"detect":[13,138],"correlation":[14],"clusters":[15,61,92,125,139,211],"able":[16,136],"analyze":[18],"dimensional":[19],"data":[20,47,67,85,160],"in":[21,36,65,68,98,103,140,178,188,223],"range":[23],"of":[24,38,84,89,124,149,181],"around":[25],"5":[26,163],"30":[28,165],"axes.":[29],"Existing":[30],"methods":[31],"typically":[32],"exhibit":[33],"super-linear":[34],"behavior":[35],"terms":[37],"space":[39,107,153],"or":[40,146],"execution":[41],"time.":[42],"MrCC":[43,176,209],"employs":[44],"novel":[46],"structure":[48],"based":[49],"on":[50,76,158],"multi-resolution":[51],"and":[52,79,87,101,109,134,167,175,184],"gains":[53],"over":[54],"previous":[55],"approaches":[56],"in:":[57],"(a)":[58],"it":[59,73,95,111],"finds":[60],"that":[62,196],"stand":[63],"out":[64],"statistical":[70],"sense;":[71],"(b)":[72],"is":[74,96,112,135],"linear":[75,97,147],"running":[77,104],"time":[78,105,179],"memory":[80,99],"usage":[81,100],"regarding":[82,106],"number":[83,123],"points":[86],"dimensionality":[88],"subspaces":[90,141],"where":[91],"exist;":[93],"(c)":[94],"quasi-linear":[102],"dimensionality;":[108],"(d)":[110],"accurate,":[113],"deterministic,":[114],"robust":[115],"noise,":[117],"does":[118,129],"not":[119,130],"require":[120],"stating":[121],"as":[126],"input":[127],"parameter,":[128],"perform":[131],"distance":[132],"calculation":[133],"generated":[142],"by":[143],"original":[144,150],"axes":[145,166],"combinations":[148],"axes,":[151],"including":[152],"rotation.":[154],"performed":[156],"experiments":[157],"synthetic":[159],"ranging":[161],"from":[162,168],"12":[169],"k":[170,173],"250":[172],"points,":[174],"outperformed":[177],"five":[180],"recent":[183],"related":[185],"work,":[186],"being":[187],"average":[189],"10":[190],"times":[191,215],"faster":[192,216],"than":[193,217],"competitors":[195],"also":[197],"presented":[198],"high":[199],"accuracy":[200,222],"results":[201],"for":[202],"every":[203],"tested":[204],"dataset.":[205],"Regarding":[206],"real":[207],"data,":[208],"found":[210],"at":[212],"least":[213],"9":[214],"competitors,":[219],"increasing":[220],"their":[221],"up":[224],"34":[226],"percent.":[227]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":9},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}