{"id":"https://openalex.org/W2046193218","doi":"https://doi.org/10.1109/vast.2012.6400493","title":"An adaptive parameter space-filling algorithm for highly interactive cluster exploration","display_name":"An adaptive parameter space-filling algorithm for highly interactive cluster exploration","publication_year":2012,"publication_date":"2012-10-01","ids":{"openalex":"https://openalex.org/W2046193218","doi":"https://doi.org/10.1109/vast.2012.6400493","mag":"2046193218"},"language":"en","primary_location":{"id":"doi:10.1109/vast.2012.6400493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vast.2012.6400493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Visual Analytics Science and Technology (VAST)","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/A5076734836","display_name":"Zafar Ahmed","orcid":null},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zafar Ahmed","raw_affiliation_strings":["School of Computer Science and Center for Spatial Analysis The University of Oklahoma"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Center for Spatial Analysis The University of Oklahoma","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084471891","display_name":"Chris Weaver","orcid":"https://orcid.org/0000-0002-6713-093X"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chris Weaver","raw_affiliation_strings":["School of Computer Science and Center for Spatial Analysis The University of Oklahoma"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Center for Spatial Analysis The University of Oklahoma","institution_ids":["https://openalex.org/I8692664"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I8692664"],"apc_list":null,"apc_paid":null,"fwci":1.1106,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.7993177,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9866999983787537,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9829000234603882,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7890421152114868},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7742538452148438},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5507904887199402},{"id":"https://openalex.org/keywords/parameter-space","display_name":"Parameter space","score":0.489803284406662},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4727295935153961},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42591020464897156},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40337151288986206},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34177619218826294},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19656944274902344},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14542704820632935}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7890421152114868},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7742538452148438},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5507904887199402},{"id":"https://openalex.org/C73586568","wikidata":"https://www.wikidata.org/wiki/Q2600211","display_name":"Parameter space","level":2,"score":0.489803284406662},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4727295935153961},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42591020464897156},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40337151288986206},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34177619218826294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19656944274902344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14542704820632935},{"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vast.2012.6400493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vast.2012.6400493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Visual Analytics Science and Technology (VAST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309482","display_name":"Oklahoma State University","ror":"https://ror.org/045ntgf29"},{"id":"https://openalex.org/F4320310179","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83"},{"id":"https://openalex.org/F4320338283","display_name":"Office of Experimental Program to Stimulate Competitive Research","ror":"https://ror.org/04k9mqs78"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1586504719","https://openalex.org/W1594453896","https://openalex.org/W1613201427","https://openalex.org/W1983362611","https://openalex.org/W2055141025","https://openalex.org/W2059907446","https://openalex.org/W2071307843","https://openalex.org/W2072252718","https://openalex.org/W2094998799","https://openalex.org/W2122441390","https://openalex.org/W2137367494","https://openalex.org/W2138199375","https://openalex.org/W2147846431","https://openalex.org/W2150864656","https://openalex.org/W2151530263","https://openalex.org/W2154462487","https://openalex.org/W2157530472","https://openalex.org/W2161133721","https://openalex.org/W2162773908","https://openalex.org/W2164223342","https://openalex.org/W2166279335","https://openalex.org/W2166706763","https://openalex.org/W2169884736","https://openalex.org/W2338049369","https://openalex.org/W3137466223","https://openalex.org/W3142947634","https://openalex.org/W3149704448","https://openalex.org/W4246962530","https://openalex.org/W4247110399","https://openalex.org/W6684647712"],"related_works":["https://openalex.org/W2068608913","https://openalex.org/W3124914020","https://openalex.org/W2141033859","https://openalex.org/W2077542787","https://openalex.org/W2156434174","https://openalex.org/W2071701083","https://openalex.org/W2383687187","https://openalex.org/W2070401501","https://openalex.org/W2081517010","https://openalex.org/W2121496884"],"abstract_inverted_index":{"For":[0],"a":[1,10,75,124,144,152,157,234],"user":[2,203],"to":[3,79,183,192,202,265,268],"perceive":[4],"continuous":[5],"interactive":[6,82],"response":[7,83],"time":[8,84,145,160],"in":[9,31,88,171,206,218,241],"visualization":[11,37],"tool,":[12],"the":[13,81,97,132,138,207,212,219,231,238],"rule":[14],"of":[15,46,61,85,92,127,143,159,165,168,195,215],"thumb":[16],"is":[17,233],"that":[18,230,256],"it":[19],"must":[20],"process,":[21],"deliver,":[22],"and":[23,44,102,119,140,150,191,275],"display":[24],"rendered":[25],"results":[26,178,260],"for":[27],"any":[28],"given":[29],"interaction":[30,101,169,181,204,213,243],"under":[32],"100":[33],"milliseconds.":[34],"In":[35,70],"many":[36],"systems,":[38],"successive":[39],"interactions":[40,110],"trigger":[41],"independent":[42],"queries":[43,51],"caching":[45],"results.":[47],"Consequently,":[48],"computationally":[49],"expensive":[50],"like":[52],"multidimensional":[53,93],"clustering":[54,87,117,189,247,259],"cannot":[55],"keep":[56],"up":[57],"with":[58,248],"rapid":[59,274],"sequences":[60,182],"interactions,":[62],"precluding":[63],"visual":[64],"benefits":[65],"such":[66],"as":[67],"motion":[68],"parallax.":[69],"this":[71],"paper,":[72],"we":[73,174],"describe":[74],"heuristic":[76],"prefetching":[77],"technique":[78],"improve":[80],"KMeans":[86],"dynamic":[89],"query":[90,104,177],"visualizations":[91],"data.":[94,162],"We":[95,129,251],"address":[96],"tradeoff":[98],"between":[99],"high":[100],"intense":[103],"computation":[105],"by":[106,137,148,210],"observing":[107],"how":[108],"related":[109],"on":[111,131,225],"overlapping":[112],"data":[113,228],"subsets":[114],"produce":[115],"similar":[116],"results,":[118],"characterizing":[120],"these":[121],"similarities":[122],"within":[123],"parameter":[125,134,172,208,220],"space":[126,135,209],"interaction.":[128,277],"focus":[130],"two-dimensional":[133],"defined":[136],"minimum":[139],"maximum":[141],"values":[142],"range":[146],"manipulated":[147],"dragging":[149],"stretching":[151],"one-dimensional":[153],"filtering":[154],"lens":[155],"over":[156,237],"plot":[158],"series":[161],"Using":[163],"calculation":[164,194],"nearest":[166],"neighbors":[167,214],"points":[170,217],"space,":[173],"reuse":[175],"partial":[176],"from":[179],"prior":[180],"calculate":[184],"both":[185],"an":[186,196],"immediate":[187],"best-effort":[188],"result":[190],"schedule":[193],"exact":[197,266],"result.":[198],"The":[199],"method":[200,232],"adapts":[201],"patterns":[205],"reprioritizing":[211],"visited":[216],"space.":[221],"A":[222],"performance":[223],"study":[224],"Mesonet":[226],"meteorological":[227],"demonstrates":[229],"significant":[235],"improvement":[236],"baseline":[239],"scheme":[240],"which":[242],"triggers":[244],"on-demand,":[245],"exact-range":[246],"LRU":[249],"caching.":[250],"also":[252],"present":[253],"initial":[254],"evidence":[255],"approximate,":[257],"temporary":[258],"are":[261],"sufficiently":[262],"accurate":[263],"(compared":[264],"results)":[267],"convey":[269],"useful":[270],"cluster":[271],"structure":[272],"during":[273],"protracted":[276]},"counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}