{"id":"https://openalex.org/W2755250176","doi":"https://doi.org/10.1109/pacificvis.2017.8031609","title":"Making many-to-many parallel coordinate plots scalable by asymmetric biclustering","display_name":"Making many-to-many parallel coordinate plots scalable by asymmetric biclustering","publication_year":2017,"publication_date":"2017-04-01","ids":{"openalex":"https://openalex.org/W2755250176","doi":"https://doi.org/10.1109/pacificvis.2017.8031609","mag":"2755250176"},"language":"en","primary_location":{"id":"doi:10.1109/pacificvis.2017.8031609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pacificvis.2017.8031609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Pacific Visualization Symposium (PacificVis)","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/A5025784757","display_name":"Hsiang\u2010Yun Wu","orcid":"https://orcid.org/0000-0003-1028-0010"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hsiang-Yun Wu","raw_affiliation_strings":["Keio University, Japan"],"affiliations":[{"raw_affiliation_string":"Keio University, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034157217","display_name":"Yusuke Niibe","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yusuke Niibe","raw_affiliation_strings":["Keio University, Japan"],"affiliations":[{"raw_affiliation_string":"Keio University, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013698523","display_name":"Kazuho Watanabe","orcid":"https://orcid.org/0000-0001-6357-5141"},"institutions":[{"id":"https://openalex.org/I136259955","display_name":"Toyohashi University of Technology","ror":"https://ror.org/04ezg6d83","country_code":"JP","type":"education","lineage":["https://openalex.org/I136259955"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuho Watanabe","raw_affiliation_strings":["Toyohashi University of Technology, Japan"],"affiliations":[{"raw_affiliation_string":"Toyohashi University of Technology, Japan","institution_ids":["https://openalex.org/I136259955"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056641267","display_name":"Shigeo Takahashi","orcid":"https://orcid.org/0000-0002-4673-577X"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shigeo Takahashi","raw_affiliation_strings":["University of Aizu, Japan"],"affiliations":[{"raw_affiliation_string":"University of Aizu, Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051655670","display_name":"Makoto Uemura","orcid":"https://orcid.org/0000-0002-7375-7405"},"institutions":[{"id":"https://openalex.org/I183792356","display_name":"Hiroshima University of Economics","ror":"https://ror.org/027b58k10","country_code":"JP","type":"education","lineage":["https://openalex.org/I183792356"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Makoto Uemura","raw_affiliation_strings":["Hiroshima University, Japan"],"affiliations":[{"raw_affiliation_string":"Hiroshima University, Japan","institution_ids":["https://openalex.org/I183792356"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016480053","display_name":"Issei Fujishiro","orcid":"https://orcid.org/0000-0002-8898-730X"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Issei Fujishiro","raw_affiliation_strings":["Keio University, Japan"],"affiliations":[{"raw_affiliation_string":"Keio University, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5025784757"],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.46672601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"305","last_page":"309"},"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9786999821662903,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9660000205039978,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/linear-subspace","display_name":"Linear subspace","score":0.7711247205734253},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.759944498538971},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5857409238815308},{"id":"https://openalex.org/keywords/biclustering","display_name":"Biclustering","score":0.5350260734558105},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5148531794548035},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5010995864868164},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4965875744819641},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4749346375465393},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.46722161769866943},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3840053379535675},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.3739173412322998},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3598312735557556},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.35875096917152405},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15547212958335876},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12659907341003418}],"concepts":[{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.7711247205734253},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.759944498538971},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5857409238815308},{"id":"https://openalex.org/C144817290","wikidata":"https://www.wikidata.org/wiki/Q2976575","display_name":"Biclustering","level":5,"score":0.5350260734558105},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5148531794548035},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5010995864868164},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4965875744819641},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4749346375465393},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.46722161769866943},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3840053379535675},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.3739173412322998},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3598312735557556},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35875096917152405},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15547212958335876},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12659907341003418},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.0},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pacificvis.2017.8031609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pacificvis.2017.8031609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Pacific Visualization Symposium (PacificVis)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W182953109","https://openalex.org/W2028678069","https://openalex.org/W2031281270","https://openalex.org/W2036328877","https://openalex.org/W2047046780","https://openalex.org/W2091554625","https://openalex.org/W2099655815","https://openalex.org/W2116153763","https://openalex.org/W2123540217","https://openalex.org/W2143475690","https://openalex.org/W2147512934","https://openalex.org/W2148329479","https://openalex.org/W2153312812","https://openalex.org/W2158870854","https://openalex.org/W2314238554","https://openalex.org/W2334555719","https://openalex.org/W4242399520","https://openalex.org/W6607412946"],"related_works":["https://openalex.org/W1974340769","https://openalex.org/W2900595096","https://openalex.org/W4289277241","https://openalex.org/W2979322793","https://openalex.org/W2765801824","https://openalex.org/W2188068678","https://openalex.org/W2157302779","https://openalex.org/W4236723217","https://openalex.org/W4226363062","https://openalex.org/W2592285132"],"abstract_inverted_index":{"Datasets":[0],"obtained":[1],"through":[2],"recently":[3],"advanced":[4],"measurement":[5],"techniques":[6],"tend":[7],"to":[8,17,40,62,89,110,121,132,151,178],"possess":[9],"a":[10,74,98,152,180],"large":[11],"number":[12],"of":[13,31,44,51,56,100,115,138,146,188],"dimensions.":[14],"This":[15,71,169],"leads":[16],"explosively":[18],"increasing":[19],"computation":[20],"costs":[21],"for":[22,79,201],"analyzing":[23],"such":[24],"datasets,":[25,46],"thus":[26],"making":[27],"formulation":[28],"and":[29,135,142,175,196],"verification":[30],"scientific":[32],"hypotheses":[33],"very":[34],"difficult.":[35],"Therefore,":[36],"an":[37],"efficient":[38],"approach":[39],"identifying":[41],"feature":[42,93,116],"subspaces":[43,50,117],"target":[45],"that":[47,84],"is,":[48],"the":[49,57,64,68,139,171,184,189],"dimension":[52,133],"variables":[53,134],"or":[54],"subsets":[55],"data":[58,76,82,136,157],"samples,":[59],"is":[60,108,130,198],"required":[61],"describe":[63],"essence":[65],"hidden":[66],"in":[67,183],"original":[69],"dataset.":[70],"paper":[72],"proposes":[73],"visual":[75,124],"mining":[77],"framework":[78,191],"supporting":[80],"semiautomatic":[81],"analysis":[83],"builds":[85],"upon":[86],"asymmetric":[87],"biclustering":[88,129],"explore":[90],"highly":[91],"correlated":[92],"subspaces.":[94],"For":[95],"this":[96,127],"purpose,":[97],"variant":[99],"parallel":[101,105,203],"coordinate":[102,106,204],"plots,":[103,107],"many-to-many":[104,202],"extended":[109],"visually":[111],"assist":[112],"appropriate":[113],"selections":[114],"as":[118,120],"well":[119],"avoid":[122],"intrinsic":[123],"clutter.":[125],"In":[126],"framework,":[128],"applied":[131],"samples":[137,158],"dataset":[140],"simultaneously":[141],"asymmetrically.":[143],"A":[144],"set":[145],"variable":[147,162],"axes":[148,163],"are":[149,164],"projected":[150],"single":[153],"composite":[154],"axis":[155],"while":[156],"between":[159],"two":[160],"consecutive":[161],"bundled":[165],"using":[166],"polygonal":[167],"strips.":[168],"makes":[170],"visualization":[172],"method":[173],"scalable":[174],"enables":[176],"it":[177,197],"play":[179],"key":[181],"role":[182],"framework.":[185],"The":[186],"effectiveness":[187],"proposed":[190],"has":[192],"been":[193],"empirically":[194],"proven,":[195],"remarkably":[199],"useful":[200],"plots.":[205]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"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"}
