{"id":"https://openalex.org/W2557901877","doi":"https://doi.org/10.1145/3006299.3006340","title":"Visualization of big high dimensional data in a three dimensional space","display_name":"Visualization of big high dimensional data in a three dimensional space","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2557901877","doi":"https://doi.org/10.1145/3006299.3006340","mag":"2557901877"},"language":"en","primary_location":{"id":"doi:10.1145/3006299.3006340","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3006299.3006340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd IEEE/ACM International Conference on Big Data Computing, Applications and Technologies","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/A5101628906","display_name":"Ying Xie","orcid":"https://orcid.org/0000-0002-6419-3986"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ying Xie","raw_affiliation_strings":["Kennesaw State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047665154","display_name":"Pooja Chenna","orcid":null},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pooja Chenna","raw_affiliation_strings":["Kennesaw State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053915143","display_name":"Jing He","orcid":null},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jing (Selena) He","raw_affiliation_strings":["Kennesaw State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103189799","display_name":"Linh Le","orcid":"https://orcid.org/0000-0002-0087-3448"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Linh Le","raw_affiliation_strings":["Kennesaw State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039171565","display_name":"Jacey Planteen","orcid":null},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jacey Planteen","raw_affiliation_strings":["Kennesaw State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University","institution_ids":["https://openalex.org/I172980758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I172980758"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"61","last_page":"66"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9968000054359436,"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":0.9968000054359436,"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":0.9954000115394592,"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9621999859809875,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.8086426854133606},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.7632982730865479},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7169367671012878},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6731457114219666},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.6426011323928833},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.6158685684204102},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5944085121154785},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5459952354431152},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5149110555648804},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.5120075345039368},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.5033103823661804},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.47593310475349426},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.45290854573249817},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.43514636158943176},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3514488935470581},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3129752278327942},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.289521187543869},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19665679335594177},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08798304200172424}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8086426854133606},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.7632982730865479},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7169367671012878},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6731457114219666},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.6426011323928833},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.6158685684204102},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5944085121154785},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5459952354431152},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5149110555648804},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.5120075345039368},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.5033103823661804},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.47593310475349426},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.45290854573249817},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.43514636158943176},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3514488935470581},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3129752278327942},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.289521187543869},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19665679335594177},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08798304200172424},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3006299.3006340","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3006299.3006340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd IEEE/ACM International Conference on Big Data Computing, Applications and Technologies","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":23,"referenced_works":["https://openalex.org/W26643119","https://openalex.org/W275890692","https://openalex.org/W1483055888","https://openalex.org/W1581406946","https://openalex.org/W1969557815","https://openalex.org/W1973041621","https://openalex.org/W1975152892","https://openalex.org/W1993990445","https://openalex.org/W2016818632","https://openalex.org/W2018413269","https://openalex.org/W2022927399","https://openalex.org/W2024919516","https://openalex.org/W2047046780","https://openalex.org/W2071949631","https://openalex.org/W2082730434","https://openalex.org/W2090658088","https://openalex.org/W2140095548","https://openalex.org/W2140221871","https://openalex.org/W2149803014","https://openalex.org/W2167287136","https://openalex.org/W2913066018","https://openalex.org/W3112073073","https://openalex.org/W4296154464"],"related_works":["https://openalex.org/W3162910294","https://openalex.org/W2196560602","https://openalex.org/W1974303229","https://openalex.org/W4295246512","https://openalex.org/W2962997812","https://openalex.org/W1692134900","https://openalex.org/W783379390","https://openalex.org/W2126442420","https://openalex.org/W3196630240","https://openalex.org/W1580499159"],"abstract_inverted_index":{"This":[0,49],"paper":[1],"studies":[2],"feasibility":[3],"and":[4,67,122],"scalable":[5,91],"computing":[6],"processes":[7],"for":[8,44,81,97,103,119],"visualizing":[9],"big":[10,106,117,127],"high":[11,46],"dimensional":[12,17,42,47],"data":[13,65,84,118,128],"in":[14,39],"a":[15,33,40,45,90,115],"3":[16,41],"space":[18,43],"by":[19,124],"using":[20],"dimension":[21,69,120],"reduction":[22,121],"techniques.":[23],"More":[24],"specifically,":[25],"we":[26,87,109],"propose":[27],"an":[28,77,99],"unsupervised":[29],"approach":[30,92],"to":[31],"compute":[32],"measure":[34,50],"that":[35],"is":[36,53],"called":[37],"visualizability":[38,52,74],"data.":[48,107,137],"of":[51,59,63,73,114,135],"computed":[54],"based":[55,93,129],"on":[56,94,130],"the":[57,60,64,82,104,112,126,131,136],"comparison":[58],"clustering":[61,79,101,133],"structures":[62],"before":[66],"after":[68],"reduction.":[70],"The":[71],"computation":[72],"requires":[75],"finding":[76,98],"optimal":[78,100],"structure":[80,102,134],"given":[83,105,116],"sets.":[85],"Therefore,":[86],"further":[88],"implement":[89],"K-Means":[95],"algorithm":[96],"Then":[108],"can":[110],"reduce":[111],"volume":[113],"visualization":[123],"sampling":[125],"discovered":[132]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}