{"id":"https://openalex.org/W2769850031","doi":"https://doi.org/10.2312/vmv.20171262","title":"User-study Based Optimization of Fast and Accurate Mahalanobis Brushing in Scatterplots","display_name":"User-study Based Optimization of Fast and Accurate Mahalanobis Brushing in Scatterplots","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2769850031","doi":"https://doi.org/10.2312/vmv.20171262","mag":"2769850031"},"language":"en","primary_location":{"id":"doi:10.2312/vmv.20171262","is_oa":true,"landing_page_url":"https://doi.org/10.2312/vmv.20171262","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.2312/vmv.20171262","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047733171","display_name":"Chaoran Fan","orcid":"https://orcid.org/0000-0003-4338-0755"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fan, Chaoran","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000755776","display_name":"Helwig Hauser","orcid":"https://orcid.org/0000-0003-0395-3192"},"institutions":[{"id":"https://openalex.org/I4432739","display_name":"University of Bergen","ror":"https://ror.org/03zga2b32","country_code":"NO","type":"education","lineage":["https://openalex.org/I4432739"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Hauser, Helwig","raw_affiliation_strings":["University of Bergen, Bergen, Norway"],"affiliations":[{"raw_affiliation_string":"University of Bergen, Bergen, Norway","institution_ids":["https://openalex.org/I4432739"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5047733171"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"77","last_page":"84"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12452","display_name":"Electrowetting and Microfluidic Technologies","score":0.9677000045776367,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.953000009059906,"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/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.8837414383888245},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7481257319450378},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.558844804763794},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32061415910720825},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32006579637527466}],"concepts":[{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.8837414383888245},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7481257319450378},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.558844804763794},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32061415910720825},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32006579637527466}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.2312/vmv.20171262","is_oa":true,"landing_page_url":"https://doi.org/10.2312/vmv.20171262","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"mag:2769850031","is_oa":false,"landing_page_url":"https://diglib.eg.org/handle/10.2312/vmv20171262","pdf_url":null,"source":{"id":"https://openalex.org/S4306421152","display_name":"Vision Modeling and Visualization","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"Vision Modeling and Visualization","raw_type":null}],"best_oa_location":{"id":"doi:10.2312/vmv.20171262","is_oa":true,"landing_page_url":"https://doi.org/10.2312/vmv.20171262","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1497740227","https://openalex.org/W1532174904","https://openalex.org/W1540596182","https://openalex.org/W1987869189","https://openalex.org/W2010891866","https://openalex.org/W2013073142","https://openalex.org/W2014268383","https://openalex.org/W2029469881","https://openalex.org/W2061696236","https://openalex.org/W2116732611","https://openalex.org/W2118020555","https://openalex.org/W2123185187","https://openalex.org/W2144988340","https://openalex.org/W2164038168","https://openalex.org/W2171073562","https://openalex.org/W2400274655","https://openalex.org/W2414613417","https://openalex.org/W2506678472","https://openalex.org/W2898309883","https://openalex.org/W2914973542"],"related_works":["https://openalex.org/W2089518423","https://openalex.org/W1513016872","https://openalex.org/W2768617563","https://openalex.org/W2795646554","https://openalex.org/W2161482986","https://openalex.org/W3046717254","https://openalex.org/W3131396379","https://openalex.org/W1969976316","https://openalex.org/W2112238384","https://openalex.org/W2996257832","https://openalex.org/W2338754561","https://openalex.org/W2509828848","https://openalex.org/W3208004775","https://openalex.org/W2998766249","https://openalex.org/W2785943270","https://openalex.org/W2105523845","https://openalex.org/W2178771153","https://openalex.org/W2886290493","https://openalex.org/W3138795538","https://openalex.org/W2896694291"],"abstract_inverted_index":{"Brushing":[0],"is":[1,18],"at":[2],"the":[3,36,52,82,100,115,118,122,140],"heart":[4],"of":[5,104,117],"most":[6],"modern":[7],"visual":[8],"analytics":[9],"solutions":[10],"with":[11,139],"coordinated,":[12],"multiple":[13],"views":[14],"and":[15,22,28,74,89,121,135],"effective":[16],"brushing":[17,76,107],"crucial":[19],"for":[20,78],"swift":[21],"efficient":[23],"processes":[24],"in":[25,41],"data":[26,33,43,93],"exploration":[27],"analysis.":[29],"Given":[30],"a":[31,42,57,61,71,95,111,129,137],"certain":[32],"subset":[34],"that":[35],"user":[37,96,119],"wishes":[38],"to":[39],"brush":[40],"visualization,":[44],"traditional":[45],"brushes":[46],"are":[47],"usually":[48],"either":[49],"accurate":[50,75],"(like":[51],"lasso)":[53],"or":[54,63],"fast":[55,73],"(e.g.,":[56],"simple":[58,112],"geometry":[59],"like":[60],"rectangle":[62],"circle).":[64],"In":[65],"this":[66],"paper,":[67],"we":[68,86],"now":[69],"present":[70],"new,":[72],"technique":[77,108],"scatterplots,":[79],"based":[80],"on":[81,110],"Mahalanobis":[83,142],"brush,":[84],"which":[85],"have":[87],"extended":[88],"then":[90],"optimized":[91],"using":[92],"from":[94],"study.":[97],"We":[98],"explain":[99],"principal,":[101],"sketchbased":[102],"model":[103],"our":[105],"new":[106],"(based":[109],"click-and-drag":[113],"interaction),":[114],"details":[116],"study":[120],"related":[123],"parameter":[124],"optimization,":[125],"as":[126,128],"well":[127],"quantitative":[130],"evaluation,":[131],"considering":[132],"efficiency,":[133],"accuracy,":[134],"also":[136],"comparison":[138],"original":[141],"brush.":[143]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
