{"id":"https://openalex.org/W1990293817","doi":"https://doi.org/10.1109/vast.2012.6400486","title":"Dis-function: Learning distance functions interactively","display_name":"Dis-function: Learning distance functions interactively","publication_year":2012,"publication_date":"2012-10-01","ids":{"openalex":"https://openalex.org/W1990293817","doi":"https://doi.org/10.1109/vast.2012.6400486","mag":"1990293817"},"language":"en","primary_location":{"id":"doi:10.1109/vast.2012.6400486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vast.2012.6400486","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/A5049577340","display_name":"Eli T. Brown","orcid":"https://orcid.org/0009-0005-2894-2432"},"institutions":[{"id":"https://openalex.org/I121934306","display_name":"Tufts University","ror":"https://ror.org/05wvpxv85","country_code":"US","type":"education","lineage":["https://openalex.org/I121934306"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Eli T. Brown","raw_affiliation_strings":["Department of Computer Science Tufts University","Department of Computer Science; Tufts University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science Tufts University","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science; Tufts University","institution_ids":["https://openalex.org/I121934306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100442542","display_name":"Jingjing Liu","orcid":"https://orcid.org/0009-0002-6277-5816"},"institutions":[{"id":"https://openalex.org/I121934306","display_name":"Tufts University","ror":"https://ror.org/05wvpxv85","country_code":"US","type":"education","lineage":["https://openalex.org/I121934306"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingjing Liu","raw_affiliation_strings":["Department of Computer Science Tufts University","Department of Computer Science; Tufts University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science Tufts University","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science; Tufts University","institution_ids":["https://openalex.org/I121934306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045379675","display_name":"Carla E. Brodley","orcid":"https://orcid.org/0009-0008-2134-6285"},"institutions":[{"id":"https://openalex.org/I121934306","display_name":"Tufts University","ror":"https://ror.org/05wvpxv85","country_code":"US","type":"education","lineage":["https://openalex.org/I121934306"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carla E. Brodley","raw_affiliation_strings":["Department of Computer Science Tufts University","Department of Computer Science; Tufts University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science Tufts University","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science; Tufts University","institution_ids":["https://openalex.org/I121934306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089451178","display_name":"Remco Chang","orcid":"https://orcid.org/0000-0002-6484-6430"},"institutions":[{"id":"https://openalex.org/I121934306","display_name":"Tufts University","ror":"https://ror.org/05wvpxv85","country_code":"US","type":"education","lineage":["https://openalex.org/I121934306"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Remco Chang","raw_affiliation_strings":["Department of Computer Science Tufts University","Department of Computer Science; Tufts University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science Tufts University","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science; Tufts University","institution_ids":["https://openalex.org/I121934306"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5049577340"],"corresponding_institution_ids":["https://openalex.org/I121934306"],"apc_list":null,"apc_paid":null,"fwci":12.4903,"has_fulltext":false,"cited_by_count":197,"citation_normalized_percentile":{"value":0.99018868,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"83","last_page":"92"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9940999746322632,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9901999831199646,"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":0.7779076099395752},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.5939379930496216},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.573529839515686},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.5594101548194885},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5538557171821594},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.505212128162384},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4791504740715027},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.45380595326423645},{"id":"https://openalex.org/keywords/distance-measures","display_name":"Distance measures","score":0.4523202180862427},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45211705565452576},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4315240681171417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3976740837097168},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3900406062602997},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17095765471458435},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13385796546936035}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7779076099395752},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.5939379930496216},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.573529839515686},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.5594101548194885},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5538557171821594},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.505212128162384},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4791504740715027},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.45380595326423645},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.4523202180862427},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45211705565452576},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4315240681171417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3976740837097168},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3900406062602997},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17095765471458435},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13385796546936035},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/vast.2012.6400486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vast.2012.6400486","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"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.294.6769","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.294.6769","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.tufts.edu/~remco/publications/2012/VAST2012-DisFunction.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W568124517","https://openalex.org/W1544007523","https://openalex.org/W1969045498","https://openalex.org/W1973968636","https://openalex.org/W2005948381","https://openalex.org/W2011735049","https://openalex.org/W2014987111","https://openalex.org/W2018653235","https://openalex.org/W2025394193","https://openalex.org/W2034694694","https://openalex.org/W2037133710","https://openalex.org/W2049633694","https://openalex.org/W2051088039","https://openalex.org/W2067752346","https://openalex.org/W2080417696","https://openalex.org/W2093357278","https://openalex.org/W2096100960","https://openalex.org/W2106053110","https://openalex.org/W2109824782","https://openalex.org/W2110654099","https://openalex.org/W2111538337","https://openalex.org/W2117154949","https://openalex.org/W2127218421","https://openalex.org/W2130556178","https://openalex.org/W2136261952","https://openalex.org/W2137736727","https://openalex.org/W2144935315","https://openalex.org/W2148694408","https://openalex.org/W2152010828","https://openalex.org/W2157364932","https://openalex.org/W2164223342","https://openalex.org/W2166583218","https://openalex.org/W2169495281","https://openalex.org/W2171073562","https://openalex.org/W2171456302","https://openalex.org/W2310245665","https://openalex.org/W2316564661","https://openalex.org/W2319824271","https://openalex.org/W2894656633","https://openalex.org/W2999575747","https://openalex.org/W4255692800","https://openalex.org/W4292023222","https://openalex.org/W6632558652","https://openalex.org/W6674531466","https://openalex.org/W6675751002","https://openalex.org/W6676757673","https://openalex.org/W6677328822","https://openalex.org/W6678914141","https://openalex.org/W6680332746","https://openalex.org/W6680962578","https://openalex.org/W6685096548","https://openalex.org/W6698603339"],"related_works":["https://openalex.org/W2129888254","https://openalex.org/W2115336194","https://openalex.org/W2019538911","https://openalex.org/W4294624291","https://openalex.org/W1996805379","https://openalex.org/W126836336","https://openalex.org/W1563946824","https://openalex.org/W2809929944","https://openalex.org/W2571943156","https://openalex.org/W2940991801"],"abstract_inverted_index":{"The":[0,111],"world's":[1],"corpora":[2],"of":[3,22,52,71,84,127,130,173,194],"data":[4,34,73,105,117,132,138,159,207,210],"grow":[5],"in":[6,33,206],"size":[7,208],"and":[8,102,155,175,184,209,212,220],"complexity":[9],"every":[10],"day,":[11],"making":[12],"it":[13],"increasingly":[14],"difficult":[15],"for":[16,30],"experts":[17],"to":[18,64,74,119,135,149,160,203],"make":[19],"sense":[20],"out":[21],"their":[23],"data.":[24,196],"Although":[25],"machine":[26],"learning":[27],"offers":[28],"algorithms":[29],"finding":[31],"patterns":[32],"automatically,":[35],"they":[36],"often":[37],"require":[38],"algorithm-specific":[39],"parameters,":[40],"such":[41],"as":[42],"an":[43,62,76,89,147,223],"appropriate":[44,77],"distance":[45,78,100,153,187],"function,":[46,79],"which":[47],"are":[48],"outside":[49],"the":[50,72,104,128,136,144,158,162,191,195],"purview":[51],"a":[53,58,68,96,107,151,170,177,181],"domain":[54],"expert.":[55],"We":[56,164],"present":[57],"system":[59,93,145,202,216],"that":[60,121,167,189,214],"allows":[61],"expert":[63],"interact":[65],"directly":[66],"with":[67,168],"visual":[69],"representation":[70],"define":[75],"thus":[80],"avoiding":[81],"direct":[82],"manipulation":[83],"obtuse":[85],"model":[86],"parameters.":[87],"Adopting":[88],"iterative":[90],"approach,":[91],"our":[92,201,215],"first":[94],"assumes":[95],"uniformly":[97],"weighted":[98],"Euclidean":[99],"function":[101,154,188],"projects":[103],"into":[106],"two-dimensional":[108],"scatterplot":[109,182],"view.":[110],"user":[112,178,227],"can":[113,179,221],"then":[114,156],"move":[115],"incorrectly-positioned":[116],"points":[118,133],"locations":[120],"reflect":[122,190],"his":[123],"or":[124,225],"her":[125],"understanding":[126],"similarity":[129],"those":[131],"relative":[134],"other":[137],"points.":[139],"Based":[140],"on":[141],"this":[142],"input,":[143],"performs":[146],"optimization":[148],"learn":[150],"new":[152],"re-projects":[157],"redraw":[161],"scatter-plot.":[163],"illustrate":[165],"empirically":[166],"only":[169],"few":[171],"iterations":[172],"interaction":[174],"optimization,":[176],"achieve":[180],"view":[183],"its":[185],"corresponding":[186],"user's":[192],"knowledge":[193],"In":[197],"addition,":[198],"we":[199],"evaluate":[200],"assess":[204],"scalability":[205],"dimension,":[211],"show":[213],"is":[217],"computationally":[218],"efficient":[219],"provide":[222],"interactive":[224],"near-interactive":[226],"experience.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":24},{"year":2020,"cited_by_count":24},{"year":2019,"cited_by_count":23},{"year":2018,"cited_by_count":23},{"year":2017,"cited_by_count":19},{"year":2016,"cited_by_count":13},{"year":2015,"cited_by_count":12},{"year":2014,"cited_by_count":22},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}
