{"id":"https://openalex.org/W2030511318","doi":"https://doi.org/10.1109/bigdata.2014.7004262","title":"Evaluating density-based motion for big data visual analytics","display_name":"Evaluating density-based motion for big data visual analytics","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2030511318","doi":"https://doi.org/10.1109/bigdata.2014.7004262","mag":"2030511318"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2014.7004262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004262","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Big Data (Big Data)","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/A5011856599","display_name":"Ronak Etemadpour","orcid":"https://orcid.org/0000-0003-1842-367X"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ronak Etemadpour","raw_affiliation_strings":["School of Information, University of Arizona","School of Information, University of Arizona#TAB#"],"affiliations":[{"raw_affiliation_string":"School of Information, University of Arizona","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"School of Information, University of Arizona#TAB#","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110157697","display_name":"Paul Murray","orcid":null},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paul Murray","raw_affiliation_strings":["Dept. of Computer Science, University of Illinois, Chicago","Department of Computer Science, University of Illinois at Chicago,#TAB#"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, University of Illinois, Chicago","institution_ids":["https://openalex.org/I39422238"]},{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Chicago,#TAB#","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075722001","display_name":"Angus G. Forbes","orcid":"https://orcid.org/0000-0002-8700-7795"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Angus Graeme Forbes","raw_affiliation_strings":["Dept. of Computer Science, University of Illinois, Chicago","Department of Computer Science, University of Illinois at Chicago,#TAB#"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, University of Illinois, Chicago","institution_ids":["https://openalex.org/I39422238"]},{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Chicago,#TAB#","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011856599"],"corresponding_institution_ids":["https://openalex.org/I138006243"],"apc_list":null,"apc_paid":null,"fwci":1.4632,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.8535373,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"93","issue":null,"first_page":"451","last_page":"460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9980000257492065,"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":0.9980000257492065,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9648000001907349,"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/T10895","display_name":"Species Distribution and Climate Change","score":0.9623000025749207,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7136712074279785},{"id":"https://openalex.org/keywords/visual-analytics","display_name":"Visual analytics","score":0.6683031320571899},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6212579607963562},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.588226318359375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5798310041427612},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5758551955223083},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5126947164535522},{"id":"https://openalex.org/keywords/interactive-visual-analysis","display_name":"Interactive visual analysis","score":0.4800111651420593},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4468803405761719},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4422876238822937},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.44158434867858887},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4361029863357544},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.41689425706863403},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4161449372768402},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3813554644584656},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.3624289333820343},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3243491053581238},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10129031538963318}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7136712074279785},{"id":"https://openalex.org/C59732488","wikidata":"https://www.wikidata.org/wiki/Q2528440","display_name":"Visual analytics","level":3,"score":0.6683031320571899},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6212579607963562},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.588226318359375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5798310041427612},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5758551955223083},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5126947164535522},{"id":"https://openalex.org/C99740376","wikidata":"https://www.wikidata.org/wiki/Q17092520","display_name":"Interactive visual analysis","level":4,"score":0.4800111651420593},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4468803405761719},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4422876238822937},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.44158434867858887},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4361029863357544},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.41689425706863403},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4161449372768402},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3813554644584656},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3624289333820343},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3243491053581238},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10129031538963318},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2014.7004262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004262","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W70900331","https://openalex.org/W1536091370","https://openalex.org/W1565377632","https://openalex.org/W1585610988","https://openalex.org/W1596382552","https://openalex.org/W1654829360","https://openalex.org/W1679931708","https://openalex.org/W1823329909","https://openalex.org/W1850774380","https://openalex.org/W1919405046","https://openalex.org/W1964874934","https://openalex.org/W1968762089","https://openalex.org/W2001141328","https://openalex.org/W2011317649","https://openalex.org/W2015755066","https://openalex.org/W2020035829","https://openalex.org/W2028003326","https://openalex.org/W2033034731","https://openalex.org/W2033403400","https://openalex.org/W2033602054","https://openalex.org/W2034719469","https://openalex.org/W2047752105","https://openalex.org/W2051767208","https://openalex.org/W2102902532","https://openalex.org/W2106244974","https://openalex.org/W2108075477","https://openalex.org/W2108230739","https://openalex.org/W2109608629","https://openalex.org/W2112179747","https://openalex.org/W2113637789","https://openalex.org/W2118527389","https://openalex.org/W2119452648","https://openalex.org/W2128021408","https://openalex.org/W2147235552","https://openalex.org/W2148870222","https://openalex.org/W2154627712","https://openalex.org/W2156990842","https://openalex.org/W2163965546","https://openalex.org/W2202808018","https://openalex.org/W2219091792","https://openalex.org/W2319824271","https://openalex.org/W2482589566","https://openalex.org/W2517824076","https://openalex.org/W2995395573","https://openalex.org/W2999729612","https://openalex.org/W3022418495","https://openalex.org/W3099839986","https://openalex.org/W4244030505","https://openalex.org/W4244657319","https://openalex.org/W4247781627","https://openalex.org/W4292023222","https://openalex.org/W6635035540","https://openalex.org/W6635376254","https://openalex.org/W6637169140","https://openalex.org/W6637268944","https://openalex.org/W6662359409","https://openalex.org/W6667338850","https://openalex.org/W6687922065","https://openalex.org/W6726520645","https://openalex.org/W6772118867","https://openalex.org/W7018778225"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W1558485007","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3127482518","https://openalex.org/W4210310791"],"abstract_inverted_index":{"A":[0],"common":[1],"strategy":[2],"for":[3,7,166,204,215,230],"encoding":[4],"multidimensional":[5,43,274],"data":[6,18,234],"visual":[8,36,73,197],"analysis":[9,235,272],"is":[10,62,96,114,137,160],"to":[11,80,116,140,156,183,187],"use":[12,178],"dimensionality":[13,92],"reduction":[14],"techniques":[15,225],"that":[16,60,176,226,243,259],"project":[17],"with":[19,153,191],"a":[20,32,65,97,148,161,231],"very":[21],"large":[22,154],"number":[23],"of":[24,41,72,99,119,128,134,143,150,179,196,217,233,273],"objects":[25],"and":[26,111,208,213,252,271],"dimensions":[27,30],"from":[28],"higher":[29],"onto":[31],"lower-dimensional":[33],"space.":[34],"In":[35],"analytics":[37,74,265],"tasks,":[38],"the":[39,42,70,88,91,104,117,120,132,135,141,144,177,205,211,269],"density":[40,89,113,142],"clusters":[44,50,105,190],"can":[45,56],"strongly":[46],"affect":[47],"how":[48,158],"these":[49],"are":[51,106],"perceived.":[52],"However,":[53],"this":[54],"feature":[55],"be":[57,184],"lost":[58],"when":[59],"dataset":[61],"projected":[63],"into":[64,263],"2D":[66,109,228],"space,":[67],"adversely":[68],"affecting":[69],"effectiveness":[71],"tasks.":[75,173,236,255],"Thus,":[76],"it":[77],"makes":[78],"sense":[79],"preserve,":[81],"as":[82,84],"far":[83],"possible,":[85],"information":[86],"about":[87],"during":[90,171],"reduction.":[93],"This":[94],"paper":[95],"study":[98],"motion-enhanced":[100],"cluster":[101,112,248,253],"perception":[102],"where":[103,131],"shown":[107],"in":[108],"scatterplots":[110,229],"mapped":[115],"motion":[118,136,159,180,262],"individual":[121],"constituent":[122],"points.":[123],"We":[124,146,174,237],"consider":[125],"different":[126,192,203,206],"types":[127,170],"density-based":[129,261],"motion,":[130],"magnitude":[133],"directly":[138],"related":[139],"clusters.":[145],"conducted":[147],"series":[149],"user":[151],"studies":[152],"datasets":[155,242],"investigate":[157],"powerful":[162],"perceptual":[163,172],"cue":[164],"well-suited":[165],"grouping":[167],"or":[168],"segmenting":[169],"found":[175],"enabled":[181],"users":[182],"easily":[185],"able":[186],"distinguish":[188],"between":[189],"densities.":[193],"The":[194],"amount":[195],"change":[198],"per":[199],"unit":[200],"time":[201],"was":[202],"motions,":[207],"we":[209,220],"describe":[210],"ranges":[212],"thresholds":[214],"each":[216],"them.":[218],"Specifically,":[219],"looked":[221],"at":[222],"two":[223],"projection":[224],"output":[227],"range":[232],"focus":[238],"on":[239],"high-dimensional,":[240],"real-world":[241],"might":[244],"require":[245],"analyses":[246],"involving":[247],"identification,":[249],"similarity":[250],"seeking,":[251],"ranking":[254],"Our":[256],"results":[257],"indicate":[258],"incorporating":[260],"visualization":[264],"systems":[266],"effectively":[267],"enables":[268],"exploration":[270],"datasets.":[275]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
