{"id":"https://openalex.org/W3167840523","doi":"https://doi.org/10.1109/access.2021.3087575","title":"Active Block Diagonal Subspace Clustering","display_name":"Active Block Diagonal Subspace Clustering","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3167840523","doi":"https://doi.org/10.1109/access.2021.3087575","mag":"3167840523"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3087575","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3087575","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09448219.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09448219.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079232286","display_name":"Ziqi Xie","orcid":"https://orcid.org/0000-0002-5258-2511"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziqi Xie","raw_affiliation_strings":["School of Computer and Control Engineering, Yantai University, Yantai, China"],"raw_orcid":"https://orcid.org/0000-0002-5258-2511","affiliations":[{"raw_affiliation_string":"School of Computer and Control Engineering, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100443577","display_name":"Lihong Wang","orcid":"https://orcid.org/0000-0003-0004-767X"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lihong Wang","raw_affiliation_strings":["School of Computer and Control Engineering, Yantai University, Yantai, China"],"raw_orcid":"https://orcid.org/0000-0003-0004-767X","affiliations":[{"raw_affiliation_string":"School of Computer and Control Engineering, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I18452120"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2492,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.56508786,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"9","issue":null,"first_page":"83976","last_page":"83992"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9961000084877014,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9882000088691711,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7268550395965576},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.655285120010376},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6158642768859863},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5900682210922241},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.5628277659416199},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5584962964057922},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.5556461811065674},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5289164781570435},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.4465731978416443},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.4436110258102417},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.4275876581668854},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.4103325605392456},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.36680126190185547},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3242120146751404},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.15800538659095764},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12022337317466736}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7268550395965576},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.655285120010376},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6158642768859863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5900682210922241},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.5628277659416199},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5584962964057922},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.5556461811065674},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5289164781570435},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.4465731978416443},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.4436110258102417},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.4275876581668854},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.4103325605392456},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.36680126190185547},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3242120146751404},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.15800538659095764},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12022337317466736},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3087575","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3087575","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09448219.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0172be980c9f4fb7ad366b018a6c09de","is_oa":true,"landing_page_url":"https://doaj.org/article/0172be980c9f4fb7ad366b018a6c09de","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 83976-83992 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3087575","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3087575","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09448219.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G212376329","display_name":null,"funder_award_id":"61773331","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8887430275","display_name":"\u9762\u5411\u6d77\u5cb8\u5e26\u6c61\u67d3\u8bc4\u4f30\u7684\u591a\u6e90\u9065\u611f\u5f71\u50cf\u7cbe\u7ec6\u5206\u7c7b\u7814\u7a76","funder_award_id":"62072391","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3167840523.pdf","grobid_xml":"https://content.openalex.org/works/W3167840523.grobid-xml"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W79405465","https://openalex.org/W141522515","https://openalex.org/W191001584","https://openalex.org/W1508464538","https://openalex.org/W1529019671","https://openalex.org/W1596382552","https://openalex.org/W1969014310","https://openalex.org/W1974758710","https://openalex.org/W1978484841","https://openalex.org/W2003217181","https://openalex.org/W2014237985","https://openalex.org/W2089609272","https://openalex.org/W2095705137","https://openalex.org/W2100346396","https://openalex.org/W2103560185","https://openalex.org/W2112796928","https://openalex.org/W2125070513","https://openalex.org/W2132914434","https://openalex.org/W2134089414","https://openalex.org/W2134342006","https://openalex.org/W2152714163","https://openalex.org/W2153839362","https://openalex.org/W2165916500","https://openalex.org/W2177347332","https://openalex.org/W2345189929","https://openalex.org/W2468752595","https://openalex.org/W2532206188","https://openalex.org/W2545016534","https://openalex.org/W2593349745","https://openalex.org/W2766176203","https://openalex.org/W2792823099","https://openalex.org/W2799479690","https://openalex.org/W2802754347","https://openalex.org/W2899431500","https://openalex.org/W2915488482","https://openalex.org/W2921133856","https://openalex.org/W2921596098","https://openalex.org/W2945077683","https://openalex.org/W2950244530","https://openalex.org/W2950626636","https://openalex.org/W2951270686","https://openalex.org/W2951418909","https://openalex.org/W2957046493","https://openalex.org/W2962726704","https://openalex.org/W2963165461","https://openalex.org/W2964051179","https://openalex.org/W2984353870","https://openalex.org/W3005339103","https://openalex.org/W3011230175","https://openalex.org/W3014964857","https://openalex.org/W3021963533","https://openalex.org/W3039516375","https://openalex.org/W3094591634","https://openalex.org/W3103988127","https://openalex.org/W3106090541","https://openalex.org/W3110577571","https://openalex.org/W3120740533","https://openalex.org/W3121769020","https://openalex.org/W4300514451","https://openalex.org/W6603183647","https://openalex.org/W6605798834","https://openalex.org/W6635376254","https://openalex.org/W6674601163","https://openalex.org/W6679849079","https://openalex.org/W6721804939"],"related_works":["https://openalex.org/W2902850141","https://openalex.org/W2607797544","https://openalex.org/W2885900820","https://openalex.org/W1556852487","https://openalex.org/W2265158691","https://openalex.org/W2032317191","https://openalex.org/W2613055102","https://openalex.org/W2136935487","https://openalex.org/W2964122166","https://openalex.org/W2011730213"],"abstract_inverted_index":{"Subspace":[0,13],"clustering":[1,14,92,170,182],"aims":[2],"to":[3,82,88,100,178],"find":[4],"clusters":[5,113],"in":[6],"the":[7,21,27,34,50,56,64,90,104,110,115,121,137,144,164],"low-dimensional":[8],"subspaces":[9,57],"for":[10,49,80],"high-dimensional":[11],"data.":[12],"with":[15],"Block":[16],"Diagonal":[17],"Representation":[18],"(BDR)":[19],"maintains":[20],"number":[22],"of":[23,26,58,103,112,117,136,146,166],"connected":[24],"components":[25],"graph":[28],"by":[29,52],"Laplacian":[30],"rank":[31],"constraint,":[32],"and":[33,63,84,114,119,143,157,159,172,183],"learned":[35,65],"affinity":[36,66],"matrix":[37,67],"shows":[38],"a":[39,46],"block":[40],"diagonal":[41],"structure,":[42],"which":[43,129],"will":[44],"achieve":[45],"good":[47],"segmentation":[48],"dataset":[51],"spectral":[53],"clustering.":[54],"However,":[55],"real":[59],"data":[60,106,123],"may":[61,68],"overlap":[62],"be":[69],"imprecise.":[70],"In":[71],"this":[72],"work,":[73],"we":[74],"propose":[75],"an":[76],"Active":[77],"learning":[78,184],"framework":[79],"BDR(ABDR)":[81],"acquire":[83,101],"incorporate":[85],"prior":[86],"knowledge":[87],"improve":[89],"subspace":[91],"performance.":[93],"An":[94],"active":[95,181],"selection":[96],"strategy":[97],"is":[98,141,148,176],"designed":[99],"labels":[102],"informative":[105],"points":[107],"from":[108],"both":[109],"skeleton":[111],"boundaries":[116],"clusters,":[118],"then":[120],"labeled":[122],"are":[124,130],"converted":[125],"into":[126,132],"pairwise":[127],"constraints,":[128],"incorporated":[131],"BDR.":[133],"The":[134],"optimization":[135],"new":[138],"objective":[139],"function":[140],"given":[142],"convergence":[145],"ABDR":[147,167,175],"discussed.":[149],"Experimental":[150],"results":[151],"on":[152,168],"three":[153],"images":[154],"datasets(MNIST,":[155],"ORL":[156],"COIL-20)":[158],"one":[160],"UCI":[161],"dataset(ISOLET)":[162],"demonstrate":[163],"effectiveness":[165],"complex":[169],"tasks":[171],"show":[173],"that":[174],"superior":[177],"multiple":[179],"state-of-the-art":[180],"techniques.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}