{"id":"https://openalex.org/W2033074184","doi":"https://doi.org/10.1109/vast.2014.7042480","title":"Feedback-driven interactive exploration of large multidimensional data supported by visual classifier","display_name":"Feedback-driven interactive exploration of large multidimensional data supported by visual classifier","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2033074184","doi":"https://doi.org/10.1109/vast.2014.7042480","mag":"2033074184"},"language":"en","primary_location":{"id":"doi:10.1109/vast.2014.7042480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vast.2014.7042480","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Conference on Visual Analytics Science and Technology (VAST)","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/A5040794392","display_name":"Michael Behrisch","orcid":"https://orcid.org/0000-0002-1102-103X"},"institutions":[{"id":"https://openalex.org/I189712700","display_name":"University of Konstanz","ror":"https://ror.org/0546hnb39","country_code":"DE","type":"education","lineage":["https://openalex.org/I189712700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Behrisch","raw_affiliation_strings":["Universit\u00e4t Konstanz, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e4t Konstanz, Germany","institution_ids":["https://openalex.org/I189712700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057823291","display_name":"Fatih Korkmaz","orcid":null},"institutions":[{"id":"https://openalex.org/I189712700","display_name":"University of Konstanz","ror":"https://ror.org/0546hnb39","country_code":"DE","type":"education","lineage":["https://openalex.org/I189712700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fatih Korkmaz","raw_affiliation_strings":["Universit\u00e4t Konstanz, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e4t Konstanz, Germany","institution_ids":["https://openalex.org/I189712700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101894423","display_name":"Lin Shao","orcid":"https://orcid.org/0000-0002-5118-9515"},"institutions":[{"id":"https://openalex.org/I189712700","display_name":"University of Konstanz","ror":"https://ror.org/0546hnb39","country_code":"DE","type":"education","lineage":["https://openalex.org/I189712700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Lin Shao","raw_affiliation_strings":["Universit\u00e4t Konstanz, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e4t Konstanz, Germany","institution_ids":["https://openalex.org/I189712700"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016219620","display_name":"Tobias Schreck","orcid":"https://orcid.org/0000-0003-0778-8665"},"institutions":[{"id":"https://openalex.org/I189712700","display_name":"University of Konstanz","ror":"https://ror.org/0546hnb39","country_code":"DE","type":"education","lineage":["https://openalex.org/I189712700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tobias Schreck","raw_affiliation_strings":["Universit\u00e4t Konstanz, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e4t Konstanz, Germany","institution_ids":["https://openalex.org/I189712700"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I189712700"],"apc_list":null,"apc_paid":null,"fwci":3.596,"has_fulltext":false,"cited_by_count":69,"citation_normalized_percentile":{"value":0.96062014,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"43","last_page":"52"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9994999766349792,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9994999766349792,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9990000128746033,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9975000023841858,"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/computer-science","display_name":"Computer science","score":0.8546409606933594},{"id":"https://openalex.org/keywords/zoom","display_name":"Zoom","score":0.6033074855804443},{"id":"https://openalex.org/keywords/relevance-feedback","display_name":"Relevance feedback","score":0.5388635396957397},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5359058976173401},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5307298302650452},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4664708077907562},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4533412754535675},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4509075880050659},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4473150670528412},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4216534495353699},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3941182792186737},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3835375905036926},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3742527663707733},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.1380404829978943}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8546409606933594},{"id":"https://openalex.org/C124913957","wikidata":"https://www.wikidata.org/wiki/Q1232548","display_name":"Zoom","level":3,"score":0.6033074855804443},{"id":"https://openalex.org/C2779532271","wikidata":"https://www.wikidata.org/wiki/Q445558","display_name":"Relevance feedback","level":4,"score":0.5388635396957397},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5359058976173401},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5307298302650452},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4664708077907562},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4533412754535675},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4509075880050659},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4473150670528412},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4216534495353699},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3941182792186737},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3835375905036926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3742527663707733},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.1380404829978943},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C78762247","wikidata":"https://www.wikidata.org/wiki/Q1273174","display_name":"Petroleum engineering","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},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C15336307","wikidata":"https://www.wikidata.org/wiki/Q1766051","display_name":"Lens (geology)","level":2,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/vast.2014.7042480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vast.2014.7042480","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Conference on Visual Analytics Science and Technology (VAST)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.691.6872","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.691.6872","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://bib.dbvis.de/uploadedFiles/VAST2014RelevanceFeedback_Final.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W335298240","https://openalex.org/W1483313504","https://openalex.org/W1516293359","https://openalex.org/W1965558308","https://openalex.org/W1966950823","https://openalex.org/W1990293817","https://openalex.org/W1992492534","https://openalex.org/W2014073269","https://openalex.org/W2028678069","https://openalex.org/W2029143245","https://openalex.org/W2031476339","https://openalex.org/W2051088039","https://openalex.org/W2061455250","https://openalex.org/W2081131647","https://openalex.org/W2082612735","https://openalex.org/W2095905764","https://openalex.org/W2101498401","https://openalex.org/W2108807072","https://openalex.org/W2109727435","https://openalex.org/W2119452648","https://openalex.org/W2121887149","https://openalex.org/W2125775272","https://openalex.org/W2138199375","https://openalex.org/W2138516811","https://openalex.org/W2139380568","https://openalex.org/W2140190241","https://openalex.org/W2168318855","https://openalex.org/W2291534001","https://openalex.org/W4213009331","https://openalex.org/W4239908238","https://openalex.org/W6676485797","https://openalex.org/W6696856454"],"related_works":["https://openalex.org/W2788595494","https://openalex.org/W2244676099","https://openalex.org/W3172556642","https://openalex.org/W3157456843","https://openalex.org/W1990150827","https://openalex.org/W2036676347","https://openalex.org/W1589307369","https://openalex.org/W2111943219","https://openalex.org/W4312723892","https://openalex.org/W2783065147"],"abstract_inverted_index":{"The":[0],"extraction":[1],"of":[2,24,37,96,104,174,222,227,239,257,267],"relevant":[3,30,52],"and":[4,135,192,208,216,260,269],"meaningful":[5],"information":[6],"from":[7,44],"multivariate":[8],"or":[9,58,61,76,111,143],"high-dimensional":[10],"data":[11,38,77,87],"is":[12,20,167,190],"a":[13,45,54,132,148,151,184,243],"challenging":[14],"problem.":[15],"One":[16],"reason":[17],"for":[18,73,84,150,214,225,265],"this":[19,240],"that":[21,168,182],"the":[22,35,94,101,105,141,187,205,210,237],"number":[23],"possible":[25],"representations,":[26],"which":[27],"might":[28],"contain":[29],"information,":[31],"grows":[32],"exponentially":[33],"with":[34,93,178],"amount":[36],"dimensions.":[39],"Also,":[40],"not":[41,137],"all":[42],"views":[43,75],"possibly":[46],"large":[47,86],"view":[48,107,153,198],"space,":[49],"are":[50,91,129],"potentially":[51,124],"to":[53,67,70,122,194],"given":[55],"analysis":[56],"task":[57],"user.":[59],"Focus+Context":[60],"Semantic":[62],"Zoom":[63],"Interfaces":[64],"can":[65],"help":[66],"some":[68],"extent":[69],"efficiently":[71],"search":[72,212],"interesting":[74,98,125,197],"segments,":[78],"yet":[79,100],"they":[80],"show":[81],"scalability":[82],"problems":[83],"very":[85],"sets.":[88],"Accordingly,":[89],"users":[90,169],"confronted":[92],"problem":[95],"identifying":[97],"views,":[99,126],"manual":[102],"exploration":[103,206,226,272],"entire":[106],"space":[108],"becomes":[109],"ineffective":[110],"even":[112],"infeasible.":[113],"While":[114],"certain":[115],"quality":[116],"metrics":[117],"have":[118],"been":[119],"proposed":[120],"recently":[121],"identify":[123],"these":[127],"often":[128],"defined":[130],"in":[131,161,255],"heuristic":[133],"way":[134],"do":[136],"take":[138],"into":[139],"account":[140],"application":[142],"user":[144],"context.":[145],"We":[146,218,235,250],"introduce":[147],"framework":[149,224,254],"feedback-driven":[152],"exploration,":[154],"inspired":[155],"by":[156,242],"relevance":[157],"feedback":[158],"approaches":[159],"used":[160,193],"Information":[162],"Retrieval.":[163],"Our":[164],"basic":[165],"idea":[166],"iteratively":[170],"express":[171],"their":[172],"notion":[173],"interestingness":[175],"when":[176],"presented":[177],"candidate":[179],"views.":[180],"From":[181],"expression,":[183],"model":[185],"representing":[186],"user's":[188],"preferences,":[189],"trained":[191],"recommend":[195],"further":[196],"candidates.":[199],"A":[200],"decision":[201],"support":[202],"system":[203],"monitors":[204],"process":[207,213],"assesses":[209],"relevance-driven":[211],"convergence":[215],"stability.":[217],"present":[219],"an":[220],"instantiation":[221],"our":[223,253],"Scatter":[228],"Plot":[229],"Spaces":[230],"based":[231],"on":[232,246],"visual":[233,271],"features.":[234],"demonstrate":[236],"effectiveness":[238],"implementation":[241],"case":[244],"study":[245],"two":[247],"real-world":[248],"datasets.":[249],"also":[251],"discuss":[252],"light":[256],"design":[258],"alternatives":[259],"point":[261],"out":[262],"its":[263],"usefulness":[264],"development":[266],"user-":[268],"context-dependent":[270],"systems.":[273]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}