{"id":"https://openalex.org/W4297094607","doi":"https://doi.org/10.1109/tvcg.2022.3209476","title":"A Unified Comparison of User Modeling Techniques for Predicting Data Interaction and Detecting Exploration Bias","display_name":"A Unified Comparison of User Modeling Techniques for Predicting Data Interaction and Detecting Exploration Bias","publication_year":2022,"publication_date":"2022-09-26","ids":{"openalex":"https://openalex.org/W4297094607","doi":"https://doi.org/10.1109/tvcg.2022.3209476","pmid":"https://pubmed.ncbi.nlm.nih.gov/36155457"},"language":"en","primary_location":{"id":"doi:10.1109/tvcg.2022.3209476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvcg.2022.3209476","pdf_url":null,"source":{"id":"https://openalex.org/S84775595","display_name":"IEEE Transactions on Visualization and Computer Graphics","issn_l":"1077-2626","issn":["1077-2626","1941-0506","2160-9306"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Visualization and Computer Graphics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5050252486","display_name":"Sunwoo Ha","orcid":"https://orcid.org/0000-0003-4205-3912"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sunwoo Ha","raw_affiliation_strings":["Washington University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Washington University, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040019133","display_name":"Shayan Monadjemi","orcid":"https://orcid.org/0000-0002-9385-5969"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shayan Monadjemi","raw_affiliation_strings":["Washington University, USA"],"raw_orcid":"https://orcid.org/0000-0002-9385-5969","affiliations":[{"raw_affiliation_string":"Washington University, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017894606","display_name":"Roman Garnett","orcid":"https://orcid.org/0000-0002-0152-5453"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roman Garnett","raw_affiliation_strings":["Washington University, USA"],"raw_orcid":"https://orcid.org/0000-0002-0152-5453","affiliations":[{"raw_affiliation_string":"Washington University, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083806955","display_name":"Alvitta Ottley","orcid":"https://orcid.org/0000-0002-9485-276X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alvitta Ottley","raw_affiliation_strings":["Washington University, USA"],"raw_orcid":"https://orcid.org/0000-0002-9485-276X","affiliations":[{"raw_affiliation_string":"Washington University, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5050252486"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8163,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.73256239,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"29","issue":"1","first_page":"483","last_page":"492"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9998999834060669,"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":0.9998999834060669,"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/T13398","display_name":"Data Analysis with R","score":0.9700000286102295,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9603999853134155,"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":0.873313307762146},{"id":"https://openalex.org/keywords/visual-analytics","display_name":"Visual analytics","score":0.7363547086715698},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6465848684310913},{"id":"https://openalex.org/keywords/interactive-visual-analysis","display_name":"Interactive visual analysis","score":0.5659224987030029},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5258655548095703},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.521623969078064},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.518932580947876},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4982626438140869},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.485965371131897},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4101996421813965},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3956986963748932}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.873313307762146},{"id":"https://openalex.org/C59732488","wikidata":"https://www.wikidata.org/wiki/Q2528440","display_name":"Visual analytics","level":3,"score":0.7363547086715698},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6465848684310913},{"id":"https://openalex.org/C99740376","wikidata":"https://www.wikidata.org/wiki/Q17092520","display_name":"Interactive visual analysis","level":4,"score":0.5659224987030029},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5258655548095703},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.521623969078064},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.518932580947876},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4982626438140869},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.485965371131897},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4101996421813965},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3956986963748932},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tvcg.2022.3209476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvcg.2022.3209476","pdf_url":null,"source":{"id":"https://openalex.org/S84775595","display_name":"IEEE Transactions on Visualization and Computer Graphics","issn_l":"1077-2626","issn":["1077-2626","1941-0506","2160-9306"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Visualization and Computer Graphics","raw_type":"journal-article"},{"id":"pmid:36155457","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36155457","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on visualization and computer graphics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8492696410","display_name":null,"funder_award_id":"OAC-2118201","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8674740844","display_name":null,"funder_award_id":"IIS-2142977","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1534477342","https://openalex.org/W1594453896","https://openalex.org/W1625504505","https://openalex.org/W1933687796","https://openalex.org/W1959365993","https://openalex.org/W1966950823","https://openalex.org/W1990401068","https://openalex.org/W1991207010","https://openalex.org/W2011111286","https://openalex.org/W2075585362","https://openalex.org/W2089355683","https://openalex.org/W2098113358","https://openalex.org/W2098613108","https://openalex.org/W2126736494","https://openalex.org/W2142493242","https://openalex.org/W2151570219","https://openalex.org/W2155806188","https://openalex.org/W2157581667","https://openalex.org/W2161243549","https://openalex.org/W2207175326","https://openalex.org/W2287207825","https://openalex.org/W2300753645","https://openalex.org/W2488113179","https://openalex.org/W2610345163","https://openalex.org/W2795407300","https://openalex.org/W2808026833","https://openalex.org/W2815772147","https://openalex.org/W2891451635","https://openalex.org/W2894294331","https://openalex.org/W2906194767","https://openalex.org/W2906640975","https://openalex.org/W2915786579","https://openalex.org/W2915829443","https://openalex.org/W2948894190","https://openalex.org/W2959136619","https://openalex.org/W3035461111","https://openalex.org/W3043559324","https://openalex.org/W3085029443","https://openalex.org/W3092931041","https://openalex.org/W3123806947","https://openalex.org/W3160312683","https://openalex.org/W3187134381","https://openalex.org/W3195550723","https://openalex.org/W3203696154","https://openalex.org/W4255375128","https://openalex.org/W6636859864","https://openalex.org/W6784850015"],"related_works":["https://openalex.org/W4210310791","https://openalex.org/W3149127250","https://openalex.org/W2158984754","https://openalex.org/W2143428259","https://openalex.org/W2081749267","https://openalex.org/W2116732611","https://openalex.org/W2080934634","https://openalex.org/W2126824079","https://openalex.org/W2564956852","https://openalex.org/W2166699593"],"abstract_inverted_index":{"The":[0],"visual":[1,62],"analytics":[2,63],"community":[3,67],"has":[4],"proposed":[5],"several":[6],"user":[7,43,106,119,149],"modeling":[8,107],"algorithms":[9,56,108],"to":[10,19,88,95],"capture":[11],"and":[12,25,72,90,103,130,144,151],"analyze":[13,123],"users'":[14],"interaction":[15,49,128],"behavior":[16],"in":[17,22,97],"order":[18],"assist":[20],"users":[21],"data":[23,39,127],"exploration":[24,33,124],"insight":[26],"generation.":[27],"For":[28],"example,":[29],"some":[30],"can":[31,37,57],"detect":[32],"biases":[34],"while":[35],"others":[36],"predict":[38],"points":[40],"that":[41,48],"the":[42,66],"will":[44],"interact":[45],"with":[46],"before":[47],"occurs.":[50],"Researchers":[51],"believe":[52],"this":[53,98],"collection":[54],"of":[55,74,117],"help":[58],"create":[59],"more":[60],"intelligent":[61],"tools.":[64],"However,":[65],"lacks":[68],"a":[69,79,114],"rigorous":[70],"evaluation":[71],"comparison":[73],"these":[75],"existing":[76],"techniques.":[77],"As":[78],"result,":[80],"there":[81],"is":[82],"limited":[83],"guidance":[84],"on":[85,110,113,137],"which":[86],"method":[87],"use":[89],"when.":[91],"Our":[92],"paper":[93],"seeks":[94],"fill":[96],"missing":[99],"gap":[100],"by":[101],"comparing":[102],"ranking":[104],"eight":[105],"based":[109],"their":[111],"performance":[112],"diverse":[115],"set":[116],"four":[118],"study":[120],"datasets.":[121],"We":[122],"bias":[125],"detection,":[126],"prediction,":[129],"algorithmic":[131],"complexity,":[132],"among":[133],"other":[134],"measures.":[135],"Based":[136],"our":[138],"findings,":[139],"we":[140],"highlight":[141],"open":[142],"challenges":[143],"new":[145],"directions":[146],"for":[147],"analyzing":[148],"interactions":[150],"visualization":[152],"provenance.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
