{"id":"https://openalex.org/W4407803346","doi":"https://doi.org/10.1080/10618600.2025.2468791","title":"A New Projection Pursuit Index for Big Data","display_name":"A New Projection Pursuit Index for Big Data","publication_year":2025,"publication_date":"2025-02-21","ids":{"openalex":"https://openalex.org/W4407803346","doi":"https://doi.org/10.1080/10618600.2025.2468791"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2025.2468791","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2025.2468791","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-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":null,"display_name":"Yajie Duan","orcid":"https://orcid.org/0000-0002-2381-7115"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]},{"id":"https://openalex.org/I4210096112","display_name":"Rutgers Sexual and Reproductive Health and Rights","ror":"https://ror.org/00rcvgx40","country_code":"NL","type":"other","lineage":["https://openalex.org/I4210096112"]}],"countries":["NL","US"],"is_corresponding":false,"raw_author_name":"Yajie Duan","raw_affiliation_strings":["Department of Statistics, Rutgers University","Department of Statistics, Rutgers University, NJ, USA"],"raw_orcid":"https://orcid.org/0000-0002-2381-7115","affiliations":[{"raw_affiliation_string":"Department of Statistics, Rutgers University","institution_ids":["https://openalex.org/I4210096112"]},{"raw_affiliation_string":"Department of Statistics, Rutgers University, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005184271","display_name":"Javier Cabrera","orcid":"https://orcid.org/0000-0003-0088-7249"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]},{"id":"https://openalex.org/I4210096112","display_name":"Rutgers Sexual and Reproductive Health and Rights","ror":"https://ror.org/00rcvgx40","country_code":"NL","type":"other","lineage":["https://openalex.org/I4210096112"]}],"countries":["NL","US"],"is_corresponding":true,"raw_author_name":"Javier Cabrera","raw_affiliation_strings":["Department of Statistics, Rutgers University","Department of Statistics, Rutgers University, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Rutgers University","institution_ids":["https://openalex.org/I4210096112"]},{"raw_affiliation_string":"Department of Statistics, Rutgers University, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020043337","display_name":"Birol Emir","orcid":"https://orcid.org/0000-0003-1787-4938"},"institutions":[{"id":"https://openalex.org/I180857899","display_name":"Pfizer (United States)","ror":"https://ror.org/01xdqrp08","country_code":"US","type":"company","lineage":["https://openalex.org/I180857899"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Birol Emir","raw_affiliation_strings":["Pfizer Inc","Pfizer Inc, New York, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pfizer Inc","institution_ids":["https://openalex.org/I180857899"]},{"raw_affiliation_string":"Pfizer Inc, New York, NY, USA","institution_ids":["https://openalex.org/I180857899"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5005184271"],"corresponding_institution_ids":["https://openalex.org/I102322142","https://openalex.org/I4210096112"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01892321,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":"4","first_page":"1566","last_page":"1577"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9700999855995178,"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"}},"topics":[{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9700999855995178,"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/T11106","display_name":"Data Management and Algorithms","score":0.9646000266075134,"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"}},{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.948199987411499,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/projection-pursuit","display_name":"Projection pursuit","score":0.8804362416267395},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.5413169860839844},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.451631635427475},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4457724392414093},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43809041380882263},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.392752081155777},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3507036566734314},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.34351271390914917},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.27647969126701355},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2340441644191742}],"concepts":[{"id":"https://openalex.org/C118038509","wikidata":"https://www.wikidata.org/wiki/Q382970","display_name":"Projection pursuit","level":2,"score":0.8804362416267395},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.5413169860839844},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.451631635427475},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4457724392414093},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43809041380882263},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.392752081155777},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3507036566734314},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.34351271390914917},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27647969126701355},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2340441644191742},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/10618600.2025.2468791","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2025.2468791","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1596442451","display_name":null,"funder_award_id":"FP00038230","funder_id":"https://openalex.org/F4320332194","funder_display_name":"Johnson and Johnson"}],"funders":[{"id":"https://openalex.org/F4320332194","display_name":"Johnson and Johnson","ror":"https://ror.org/03qd7mz70"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W127216130","https://openalex.org/W150071598","https://openalex.org/W655089096","https://openalex.org/W1925612170","https://openalex.org/W1963801390","https://openalex.org/W1964724001","https://openalex.org/W1978841917","https://openalex.org/W1988224587","https://openalex.org/W1997320786","https://openalex.org/W2015562474","https://openalex.org/W2058440261","https://openalex.org/W2082612735","https://openalex.org/W2090445392","https://openalex.org/W2126470108","https://openalex.org/W2128707434","https://openalex.org/W2137295153","https://openalex.org/W2884964182","https://openalex.org/W3215143317","https://openalex.org/W4232576706","https://openalex.org/W4238957295","https://openalex.org/W4366381851","https://openalex.org/W4394748744","https://openalex.org/W6628861877","https://openalex.org/W6852152800"],"related_works":["https://openalex.org/W4253679632","https://openalex.org/W2312487961","https://openalex.org/W2371601355","https://openalex.org/W2367397236","https://openalex.org/W2373463565","https://openalex.org/W2329220454","https://openalex.org/W2354037709","https://openalex.org/W2788448464","https://openalex.org/W1772501953","https://openalex.org/W2352640762"],"abstract_inverted_index":{"Visualization":[0],"of":[1,19,54,96,149,169,195],"extremely":[2],"large":[3,72,159],"datasets,":[4],"whether":[5],"in":[6,23,118,189],"static":[7,196],"or":[8],"dynamic":[9,78,94,198],"form,":[10],"poses":[11],"a":[12,31,77,93,150],"significant":[13],"challenge":[14],"due":[15],"to":[16,59,91,105,131,140,184],"the":[17,107,119,126,147,163,170,186,190,203],"limitations":[18],"most":[20],"traditional":[21],"methods":[22],"handling":[24],"big-data":[25,132,215,221],"problems.":[26],"To":[27],"address":[28],"this":[29,55,226],"challenge,":[30],"novel":[32],"visualization":[33],"approach":[34,130],"for":[35,81,143,210,220,225],"big":[36,144,179],"data":[37,108,151,165,180],"is":[38,58,138,173,182],"proposed":[39,171,204],"based":[40,201],"on":[41,175,202],"Projection":[42,85,101,112,205],"Pursuit,":[43],"Grand":[44,88],"and":[45,48,67,87,197],"Guided":[46,75,128],"Tours,":[47],"Data":[49],"Nuggets":[50],"methods.":[51],"The":[52,74,167,193],"aim":[53],"new":[56,135,187],"methodology":[57,172],"discover":[60],"hidden":[61],"structures":[62,70,213],"such":[63],"as":[64],"clusters,":[65],"outliers,":[66],"other":[68],"nonlinear":[69,212],"within":[71,214],"datasets.":[73,177],"Tour,":[76],"graphical":[79,199],"tool":[80],"high-dimensional":[82],"data,":[83,145],"integrates":[84],"Pursuit":[86,102,113,206],"Tour":[89,129],"techniques":[90],"present":[92],"sequence":[95],"low-dimensional":[97],"projections":[98],"obtained":[99],"by":[100],"index":[103,137,207],"functions":[104],"navigate":[106],"space.":[109],"While":[110],"various":[111],"indices":[114],"have":[115],"been":[116],"developed":[117,139],"past,":[120],"computational":[121],"constraints":[122],"arise":[123],"when":[124],"applying":[125],"original":[127,164],"scenarios.":[133],"A":[134,178],"PP":[136],"be":[141],"computable":[142],"with":[146],"help":[148],"compression":[152],"method":[153,188],"called":[154],"\u201cData":[155],"Nuggets\u201d":[156],"that":[157],"reduces":[158],"datasets":[160],"while":[161],"maintaining":[162],"structure.":[166],"effectiveness":[168],"demonstrated":[174],"simulated":[176],"application":[181],"presented":[183],"illustrate":[185],"real":[191],"world.":[192],"development":[194],"tools":[200],"holds":[208],"promise":[209],"detecting":[211],"contexts,":[216],"offering":[217],"valuable":[218],"insights":[219],"analysis.":[222],"Supplementary":[223],"materials":[224],"article":[227],"are":[228],"available":[229],"online.":[230]},"counts_by_year":[],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2025-10-10T00:00:00"}
