{"id":"https://openalex.org/W1983362611","doi":"https://doi.org/10.1109/vast.2009.5332629","title":"Two-stage framework for visualization of clustered high dimensional data","display_name":"Two-stage framework for visualization of clustered high dimensional data","publication_year":2009,"publication_date":"2009-01-01","ids":{"openalex":"https://openalex.org/W1983362611","doi":"https://doi.org/10.1109/vast.2009.5332629","mag":"1983362611"},"language":"en","primary_location":{"id":"doi:10.1109/vast.2009.5332629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vast.2009.5332629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Symposium on Visual Analytics Science and Technology","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/A5047912015","display_name":"Jaegul Choo","orcid":"https://orcid.org/0000-0003-1071-4835"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jaegul Choo","raw_affiliation_strings":["College of Computing, Georgia Institute of Technology, Atlanta, GA, USA","College of Computing, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, 30332, USA"],"affiliations":[{"raw_affiliation_string":"College of Computing, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"College of Computing, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, 30332, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110192503","display_name":"Shawn Bohn","orcid":null},"institutions":[{"id":"https://openalex.org/I142606810","display_name":"Pacific Northwest National Laboratory","ror":"https://ror.org/05h992307","country_code":"US","type":"facility","lineage":["https://openalex.org/I1325736334","https://openalex.org/I1330989302","https://openalex.org/I142606810","https://openalex.org/I39565521"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shawn Bohn","raw_affiliation_strings":["National Visualization and Analytics Center, Pacific Northwest National Laboratory, Richland, WA, USA","National Visualization and Analytics Center, Pacific Northwest National Laboratory, 902 Battelle Blvd, Richland, WA 99354, USA"],"affiliations":[{"raw_affiliation_string":"National Visualization and Analytics Center, Pacific Northwest National Laboratory, Richland, WA, USA","institution_ids":["https://openalex.org/I142606810"]},{"raw_affiliation_string":"National Visualization and Analytics Center, Pacific Northwest National Laboratory, 902 Battelle Blvd, Richland, WA 99354, USA","institution_ids":["https://openalex.org/I142606810"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101728710","display_name":"Haesun Park","orcid":"https://orcid.org/0000-0001-6259-7170"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haesun Park","raw_affiliation_strings":["College of Computing, Georgia Institute of Technology, Atlanta, GA, USA","College of Computing, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, 30332, USA"],"affiliations":[{"raw_affiliation_string":"College of Computing, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"College of Computing, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, 30332, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5047912015"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":6.7744,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.96604086,"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":"67","last_page":"74"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9940000176429749,"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":0.9940000176429749,"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/T10799","display_name":"Data Visualization and Analytics","score":0.984499990940094,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9797000288963318,"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/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.8773705959320068},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.7446022629737854},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.7161483764648438},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6939096450805664},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.6264063119888306},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6188058257102966},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.6045090556144714},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5561472177505493},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4521324038505554},{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.45104289054870605},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42565304040908813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4039417803287506},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2954024076461792}],"concepts":[{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.8773705959320068},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.7446022629737854},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.7161483764648438},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6939096450805664},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.6264063119888306},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6188058257102966},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.6045090556144714},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5561472177505493},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4521324038505554},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.45104289054870605},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42565304040908813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4039417803287506},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2954024076461792},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/vast.2009.5332629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vast.2009.5332629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Symposium on Visual Analytics Science and Technology","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.212.6782","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.212.6782","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cc.gatech.edu/~hpark/papers/choo_vast09.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.332.690","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.690","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://fodava.gatech.edu/files/reports/FODAVA-09-07.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7099999785423279,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W121371952","https://openalex.org/W1515529865","https://openalex.org/W1554944419","https://openalex.org/W1679913846","https://openalex.org/W1761337995","https://openalex.org/W1971784203","https://openalex.org/W1985809919","https://openalex.org/W2001141328","https://openalex.org/W2012352340","https://openalex.org/W2027077102","https://openalex.org/W2053186076","https://openalex.org/W2113041963","https://openalex.org/W2125282628","https://openalex.org/W2135346934","https://openalex.org/W2146820706","https://openalex.org/W2148694408","https://openalex.org/W2164338948","https://openalex.org/W2171033594","https://openalex.org/W2171347282","https://openalex.org/W2319660501","https://openalex.org/W2511353375","https://openalex.org/W2973651390","https://openalex.org/W3033414884","https://openalex.org/W3120740533","https://openalex.org/W4237546126","https://openalex.org/W4245176872"],"related_works":["https://openalex.org/W2169311637","https://openalex.org/W2151015462","https://openalex.org/W2380927352","https://openalex.org/W2111149694","https://openalex.org/W1623999640","https://openalex.org/W2011753777","https://openalex.org/W2980846366","https://openalex.org/W2037772955","https://openalex.org/W32502520","https://openalex.org/W2370292837"],"abstract_inverted_index":{"In":[0,30,79],"this":[1,126],"paper,":[2],"we":[3,34,128],"discuss":[4],"dimension":[5,27,44,67,84,95,119],"reduction":[6,28,45,96],"methods":[7],"for":[8,21,90],"2D":[9],"visualization":[10,91],"of":[11,60,105,113],"high":[12],"dimensional":[13,38],"clustered":[14],"data.":[15],"We":[16],"propose":[17,129],"a":[18,42],"two-stage":[19,131],"framework":[20],"visualizing":[22],"such":[23,47,98],"data":[24,39,149],"based":[25],"on":[26,69,143],"methods.":[29],"the":[31,36,54,70,80,83,106,111,118,121],"first":[32],"stage,":[33,82],"obtain":[35],"reduced":[37,66,87],"by":[40,93],"applying":[41],"supervised":[43],"method":[46,97],"as":[48,99,138,140],"linear":[49],"discriminant":[50],"analysis":[51],"which":[52],"preserves":[53],"original":[55],"cluster":[56],"structure":[57],"in":[58],"terms":[59],"its":[61],"criteria.":[62],"The":[63,103],"resulting":[64],"optimal":[65],"depends":[68],"optimization":[71],"criteria":[72],"and":[73,133,146],"is":[74,85,108],"often":[75],"larger":[76],"than":[77],"2.":[78,124],"second":[81],"further":[86],"to":[88,109,116,123],"2":[89],"purposes":[92],"another":[94],"principal":[100],"component":[101],"analysis.":[102],"role":[104],"second-stage":[107],"minimize":[110],"loss":[112],"information":[114],"due":[115],"reducing":[117],"all":[120],"way":[122],"Using":[125],"framework,":[127],"several":[130],"methods,":[132],"present":[134],"their":[135],"theoretical":[136],"characteristics":[137],"well":[139],"experimental":[141],"comparisons":[142],"both":[144],"artificial":[145],"real-world":[147],"text":[148],"sets.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":5}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
