{"id":"https://openalex.org/W3025752507","doi":"https://doi.org/10.1109/tnnls.2020.2991366","title":"Simultaneous Global and Local Graph Structure Preserving for Multiple Kernel Clustering","display_name":"Simultaneous Global and Local Graph Structure Preserving for Multiple Kernel Clustering","publication_year":2020,"publication_date":"2020-05-13","ids":{"openalex":"https://openalex.org/W3025752507","doi":"https://doi.org/10.1109/tnnls.2020.2991366","mag":"3025752507","pmid":"https://pubmed.ncbi.nlm.nih.gov/32406846"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2020.2991366","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.2991366","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","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/A5068223297","display_name":"Zhenwen Ren","orcid":"https://orcid.org/0000-0003-3791-9750"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]},{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhenwen Ren","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","School of National Defence Science and Technology, Southwest University of Science and Technology, Mianyang, China"],"raw_orcid":"https://orcid.org/0000-0003-3791-9750","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"School of National Defence Science and Technology, Southwest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034434932","display_name":"Quansen Sun","orcid":"https://orcid.org/0000-0001-6019-1986"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quansen Sun","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-6019-1986","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5068223297"],"corresponding_institution_ids":["https://openalex.org/I1297991670","https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":9.5143,"has_fulltext":false,"cited_by_count":151,"citation_normalized_percentile":{"value":0.98571003,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"32","issue":"5","first_page":"1839","last_page":"1851"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9979000091552734,"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/T10057","display_name":"Face and Expression Recognition","score":0.9979000091552734,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9923999905586243,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multiple-kernel-learning","display_name":"Multiple kernel learning","score":0.8456975221633911},{"id":"https://openalex.org/keywords/kernel-embedding-of-distributions","display_name":"Kernel embedding of distributions","score":0.6802064180374146},{"id":"https://openalex.org/keywords/tree-kernel","display_name":"Tree kernel","score":0.6683251261711121},{"id":"https://openalex.org/keywords/graph-kernel","display_name":"Graph kernel","score":0.6615986227989197},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6472856402397156},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.646178126335144},{"id":"https://openalex.org/keywords/radial-basis-function-kernel","display_name":"Radial basis function kernel","score":0.5225821733474731},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5208895206451416},{"id":"https://openalex.org/keywords/string-kernel","display_name":"String kernel","score":0.5181697607040405},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.47737690806388855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4670874774456024},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4633871018886566},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.4608321785926819},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.4559178948402405},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3767203092575073},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33933401107788086},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3277294635772705},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.259149432182312},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.14499664306640625},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07041183114051819}],"concepts":[{"id":"https://openalex.org/C2776879701","wikidata":"https://www.wikidata.org/wiki/Q25048660","display_name":"Multiple kernel learning","level":4,"score":0.8456975221633911},{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.6802064180374146},{"id":"https://openalex.org/C140417398","wikidata":"https://www.wikidata.org/wiki/Q16933942","display_name":"Tree kernel","level":5,"score":0.6683251261711121},{"id":"https://openalex.org/C100595998","wikidata":"https://www.wikidata.org/wiki/Q11731931","display_name":"Graph kernel","level":5,"score":0.6615986227989197},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6472856402397156},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.646178126335144},{"id":"https://openalex.org/C75866337","wikidata":"https://www.wikidata.org/wiki/Q7280263","display_name":"Radial basis function kernel","level":4,"score":0.5225821733474731},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5208895206451416},{"id":"https://openalex.org/C55851704","wikidata":"https://www.wikidata.org/wiki/Q7623983","display_name":"String kernel","level":5,"score":0.5181697607040405},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.47737690806388855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4670874774456024},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4633871018886566},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.4608321785926819},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.4559178948402405},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3767203092575073},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33933401107788086},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3277294635772705},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.259149432182312},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.14499664306640625},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07041183114051819}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2020.2991366","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.2991366","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:32406846","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32406846","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 neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2566969144","display_name":null,"funder_award_id":"JCKY2017209B010","funder_id":"https://openalex.org/F4320325551","funder_display_name":"National Defense Pre-Research Foundation of China"},{"id":"https://openalex.org/G3187417473","display_name":null,"funder_award_id":"JCKY2018209B001","funder_id":"https://openalex.org/F4320325551","funder_display_name":"National Defense Pre-Research Foundation of China"},{"id":"https://openalex.org/G3830962517","display_name":null,"funder_award_id":"61673220","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7239605087","display_name":null,"funder_award_id":"BK20190440","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G7831906081","display_name":null,"funder_award_id":"61906091","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"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320325551","display_name":"National Defense Pre-Research Foundation of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W79405465","https://openalex.org/W219179425","https://openalex.org/W1968678306","https://openalex.org/W1979089718","https://openalex.org/W1993962865","https://openalex.org/W2014277868","https://openalex.org/W2017441234","https://openalex.org/W2019337445","https://openalex.org/W2073161435","https://openalex.org/W2081549451","https://openalex.org/W2087714402","https://openalex.org/W2126761607","https://openalex.org/W2147278762","https://openalex.org/W2168901348","https://openalex.org/W2170590171","https://openalex.org/W2209159500","https://openalex.org/W2234634182","https://openalex.org/W2366739890","https://openalex.org/W2422268042","https://openalex.org/W2528144785","https://openalex.org/W2532206188","https://openalex.org/W2575689894","https://openalex.org/W2577472518","https://openalex.org/W2579597427","https://openalex.org/W2606024481","https://openalex.org/W2614970963","https://openalex.org/W2728364730","https://openalex.org/W2740464254","https://openalex.org/W2743926534","https://openalex.org/W2758611985","https://openalex.org/W2765158981","https://openalex.org/W2766053647","https://openalex.org/W2795051509","https://openalex.org/W2797647736","https://openalex.org/W2800615729","https://openalex.org/W2883604340","https://openalex.org/W2886265585","https://openalex.org/W2887268518","https://openalex.org/W2888654602","https://openalex.org/W2892151043","https://openalex.org/W2893652381","https://openalex.org/W2893830906","https://openalex.org/W2896169497","https://openalex.org/W2897582990","https://openalex.org/W2898541610","https://openalex.org/W2901373116","https://openalex.org/W2903321361","https://openalex.org/W2908035133","https://openalex.org/W2954752948","https://openalex.org/W2962702700","https://openalex.org/W2963051348","https://openalex.org/W2963165461","https://openalex.org/W2964169082","https://openalex.org/W2969633497","https://openalex.org/W3122534566","https://openalex.org/W6603183647","https://openalex.org/W6681738144","https://openalex.org/W6717810817","https://openalex.org/W6727872839","https://openalex.org/W6731795620","https://openalex.org/W6731811539","https://openalex.org/W6745981979"],"related_works":["https://openalex.org/W3013206934","https://openalex.org/W4291669689","https://openalex.org/W2130792056","https://openalex.org/W2041351400","https://openalex.org/W3100948281","https://openalex.org/W2963372274","https://openalex.org/W4300176214","https://openalex.org/W2294612767","https://openalex.org/W2141199622","https://openalex.org/W1970940244"],"abstract_inverted_index":{"Multiple":[0],"kernel":[1,12,53,93,101,110,114,125,131,137,155,182],"learning":[2,13,34,141],"(MKL)":[3],"is":[4,55,63,85,168],"generally":[5],"recognized":[6],"to":[7,22,77,105,143,170,194],"perform":[8],"better":[9],"than":[10,159],"single":[11],"(SKL)":[14],"in":[15,52,87,154,215],"handling":[16],"nonlinear":[17],"clustering":[18,40,73,94,205,213,218],"problem,":[19,80],"largely":[20,56],"thanks":[21],"MKL":[23,38,60,83,212],"avoids":[24],"selecting":[25],"and":[26,135,147,183,203,220],"tuning":[27],"predefined":[28,113],"kernel.":[29],"By":[30],"integrating":[31],"the":[32,36,47,145,151,160,172,180,184,196,210],"self-expression":[33],"framework,":[35],"graph-based":[37],"subspace":[39],"has":[41],"recently":[42],"attracted":[43],"considerable":[44],"attention.":[45],"However,":[46],"graph":[48,69,186],"structure":[49,140,149],"of":[50,67,150,192,217],"data":[51,153],"space":[54],"ignored":[57],"by":[58],"previous":[59],"methods,":[61],"which":[62,116,177],"a":[64,81,99,112,119,130,136],"key":[65],"concept":[66],"affinity":[68,185],"construction":[70],"for":[71,122],"spectral":[72],"purposes.":[74],"In":[75,163],"order":[76],"address":[78],"this":[79,88],"novel":[82],"method":[84],"proposed":[86,169],"article,":[89],"namely,":[90],"structure-preserving":[91],"multiple":[92],"(SPMKC).":[95],"Specifically,":[96],"SPMKC":[97,128,208],"proposes":[98,129],"new":[100],"affine":[102],"weight":[103,121],"strategy":[104],"learn":[106],"an":[107,165],"optimal":[108],"consensus":[109,181],"from":[111],"pool,":[115],"can":[117],"assign":[118],"suitable":[120],"each":[123,191],"base":[124],"automatically.":[126],"Furthermore,":[127],"group":[132],"self-expressiveness":[133],"term":[134,142],"adaptive":[138],"local":[139,148],"preserve":[144],"global":[146],"input":[152],"space,":[156],"respectively,":[157],"rather":[158],"original":[161],"space.":[162],"addition,":[164],"efficient":[166],"algorithm":[167],"solve":[171],"resulting":[173],"unified":[174],"objective":[175],"function,":[176],"iteratively":[178],"updates":[179],"so":[187],"that":[188,207],"collaboratively":[189],"promoting":[190],"them":[193],"reach":[195],"optimum":[197],"condition.":[198],"Experiments":[199],"on":[200],"both":[201],"image":[202],"text":[204],"demonstrate":[206],"outperforms":[209],"state-of-the-art":[211],"methods":[214],"terms":[216],"performance":[219],"computational":[221],"cost.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":42},{"year":2022,"cited_by_count":27},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":1}],"updated_date":"2026-05-29T09:21:14.243279","created_date":"2025-10-10T00:00:00"}
