{"id":"https://openalex.org/W2886788651","doi":"https://doi.org/10.1109/dsw.2018.8439916","title":"SUBSPACE DATA VISUALIZATION WITH DISSIMILARITY BASED ON PRINCIPAL ANGLE","display_name":"SUBSPACE DATA VISUALIZATION WITH DISSIMILARITY BASED ON PRINCIPAL ANGLE","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2886788651","doi":"https://doi.org/10.1109/dsw.2018.8439916","mag":"2886788651"},"language":"en","primary_location":{"id":"doi:10.1109/dsw.2018.8439916","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsw.2018.8439916","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Data Science Workshop (DSW)","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/A5003439795","display_name":"Xinyue Shen","orcid":"https://orcid.org/0000-0001-7760-0897"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyue Shen","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, CHINA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, CHINA","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083048260","display_name":"Yuchen Jiao","orcid":"https://orcid.org/0000-0002-0976-8070"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuchen Jiao","raw_affiliation_strings":["Tsinghua University, Beijing, Beijing, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100621681","display_name":"Yuantao Gu","orcid":"https://orcid.org/0000-0002-8427-1021"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuantao Gu","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, CHINA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, CHINA","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.106,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.45012747,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"46","issue":null,"first_page":"16","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9973000288009644,"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":0.9973000288009644,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9829000234603882,"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/T10057","display_name":"Face and Expression Recognition","score":0.982699990272522,"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/linear-subspace","display_name":"Linear subspace","score":0.8331737518310547},{"id":"https://openalex.org/keywords/multidimensional-scaling","display_name":"Multidimensional scaling","score":0.693396270275116},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6302978992462158},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5863396525382996},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5837809443473816},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5556775331497192},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.5481215119361877},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5278629660606384},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5278382301330566},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5102484226226807},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.501476526260376},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4512452781200409},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4470958113670349},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4446474313735962},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4441673159599304},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4378192722797394},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2677431106567383},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1351241171360016},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.10333308577537537},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08948558568954468}],"concepts":[{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.8331737518310547},{"id":"https://openalex.org/C91682802","wikidata":"https://www.wikidata.org/wiki/Q620538","display_name":"Multidimensional scaling","level":2,"score":0.693396270275116},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6302978992462158},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5863396525382996},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5837809443473816},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5556775331497192},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.5481215119361877},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5278629660606384},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5278382301330566},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5102484226226807},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.501476526260376},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4512452781200409},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4470958113670349},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4446474313735962},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4441673159599304},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4378192722797394},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2677431106567383},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1351241171360016},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.10333308577537537},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08948558568954468},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsw.2018.8439916","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsw.2018.8439916","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Data Science Workshop (DSW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W82947326","https://openalex.org/W1530159900","https://openalex.org/W1540016502","https://openalex.org/W1606778734","https://openalex.org/W1950520880","https://openalex.org/W1973683994","https://openalex.org/W1993962865","https://openalex.org/W2003217181","https://openalex.org/W2009234819","https://openalex.org/W2013712253","https://openalex.org/W2028678069","https://openalex.org/W2031281270","https://openalex.org/W2085261163","https://openalex.org/W2090287317","https://openalex.org/W2118154608","https://openalex.org/W2123921160","https://openalex.org/W2125874614","https://openalex.org/W2139054653","https://openalex.org/W2140190241","https://openalex.org/W2146610201","https://openalex.org/W2151530263","https://openalex.org/W2152461258","https://openalex.org/W2177347332","https://openalex.org/W2345907131","https://openalex.org/W2539912446","https://openalex.org/W2551087110","https://openalex.org/W2561426102","https://openalex.org/W2607365582","https://openalex.org/W2948033325","https://openalex.org/W2963346868","https://openalex.org/W3099880660","https://openalex.org/W4252316495","https://openalex.org/W6603381056","https://openalex.org/W6640861363","https://openalex.org/W6652584071","https://openalex.org/W6680653881","https://openalex.org/W6728799417","https://openalex.org/W6762916811","https://openalex.org/W6834473044"],"related_works":["https://openalex.org/W3100286349","https://openalex.org/W2896134808","https://openalex.org/W4289378085","https://openalex.org/W4294291164","https://openalex.org/W3172436493","https://openalex.org/W1887135636","https://openalex.org/W4287164812","https://openalex.org/W2386063599","https://openalex.org/W1975884855","https://openalex.org/W3213150849"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3],"aim":[4],"to":[5,22,90],"visualize":[6],"data":[7,59,67,133],"points":[8,60],"distributing":[9],"on":[10,51,130],"a":[11,16,42,92,95],"union":[12],"of":[13,44,58,71,137],"subspaces":[14,101],"in":[15,28,104,127],"two":[17],"or":[18],"three":[19],"dimensional":[20],"plot":[21],"demonstrate":[23],"both":[24,52,79,131,151],"the":[25,29,32,35,53,62,80,83,105,112,152,159],"pairwise":[26],"angles":[27,54,64],"dataset":[30],"and":[31,61,69,82,87,111,134,140,150,158],"relation":[33,160],"among":[34,46,161],"latent":[36],"subspaces.":[37,74],"Our":[38],"main":[39],"contribution":[40],"is":[41,49,88,125],"definition":[43],"dissimilarity":[45,77,114],"data,":[47],"which":[48,143],"based":[50],"between":[55,65],"every":[56,66,156],"pair":[57],"principal":[63],"point":[68],"each":[70],"these":[72],"intrinsic":[73,100],"The":[75,99,123],"defined":[76,113],"depicts":[78],"inter-class":[81],"intra-class":[84],"angular":[85],"structures,":[86],"proven":[89],"be":[91,117],"semi-metric":[93],"with":[94],"relaxed":[96],"triangle":[97],"inequality.":[98],"are":[102,144,164],"obtained":[103],"preprocessing":[106],"step":[107],"by":[108,120],"subspace":[109,148],"clustering,":[110],"matrix":[115],"can":[116],"directly":[118],"visualized":[119,145],"multidimensional":[121],"scaling.":[122],"effectiveness":[124],"verified":[126],"numerical":[128],"experiments":[129],"synthetic":[132],"real-world":[135],"datasets":[136],"facial":[138],"images":[139],"human":[141],"motions,":[142],"into":[146],"several":[147],"clusters,":[149],"sequence":[153],"order":[154],"within":[155],"cluster":[157],"different":[162],"clusters":[163],"well":[165],"illustrated.":[166]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
