{"id":"https://openalex.org/W4412170741","doi":"https://doi.org/10.1109/tbdata.2025.3588078","title":"Multi-View Spectral Clustering on the Grassmannian Manifold With Hypergraph Representation","display_name":"Multi-View Spectral Clustering on the Grassmannian Manifold With Hypergraph Representation","publication_year":2025,"publication_date":"2025-07-10","ids":{"openalex":"https://openalex.org/W4412170741","doi":"https://doi.org/10.1109/tbdata.2025.3588078"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2025.3588078","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2025.3588078","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2503.06066","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076211698","display_name":"Murong Yang","orcid":"https://orcid.org/0000-0002-1014-9680"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Murong Yang","raw_affiliation_strings":["Department of Mathematics, College of Sciences, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, College of Sciences, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063863772","display_name":"Shihui Ying","orcid":"https://orcid.org/0000-0001-9423-0146"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shihui Ying","raw_affiliation_strings":["Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100734030","display_name":"Xin\u2010Jian Xu","orcid":"https://orcid.org/0000-0001-6088-976X"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]},{"id":"https://openalex.org/I4210121403","display_name":"Xing Wei College","ror":"https://ror.org/01xn6em86","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210121403"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin-Jian Xu","raw_affiliation_strings":["Qian Weichang College, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Qian Weichang College, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I4210121403","https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yue Gao","orcid":"https://orcid.org/0000-0002-4971-590X"},"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":"Yue Gao","raw_affiliation_strings":["BNRist, KLISS, School of Software, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"BNRist, KLISS, School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5076211698"],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":1.2015,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.80628697,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"11","issue":"6","first_page":"3185","last_page":"3196"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9865999817848206,"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":0.9865999817848206,"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":0.9592000246047974,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9279999732971191,"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/grassmannian","display_name":"Grassmannian","score":0.8265383243560791},{"id":"https://openalex.org/keywords/hypergraph","display_name":"Hypergraph","score":0.8198925256729126},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.629197359085083},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6167609095573425},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5881655812263489},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.539636492729187},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.44655975699424744},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3888310492038727},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34851133823394775},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3033628463745117},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.21711501479148865}],"concepts":[{"id":"https://openalex.org/C162929932","wikidata":"https://www.wikidata.org/wiki/Q129638","display_name":"Grassmannian","level":2,"score":0.8265383243560791},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.8198925256729126},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.629197359085083},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6167609095573425},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5881655812263489},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.539636492729187},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.44655975699424744},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3888310492038727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34851133823394775},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3033628463745117},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.21711501479148865},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tbdata.2025.3588078","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2025.3588078","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Big Data","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2503.06066","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.06066","pdf_url":"https://arxiv.org/pdf/2503.06066","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2503.06066","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.06066","pdf_url":"https://arxiv.org/pdf/2503.06066","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5531783719","display_name":null,"funder_award_id":"12071281","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":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4376608589","https://openalex.org/W1537073411","https://openalex.org/W1948107826","https://openalex.org/W3138003926","https://openalex.org/W1630514295","https://openalex.org/W4300037846","https://openalex.org/W4288275998","https://openalex.org/W2914946164","https://openalex.org/W4404954957","https://openalex.org/W1482912984"],"abstract_inverted_index":{"Graph-based":[0],"multi-view":[1,65,137,146],"spectral":[2,24,67,71],"clustering":[3,72,147,162],"methods":[4],"have":[5],"achieved":[6],"notable":[7],"progress":[8],"recently,":[9],"yet":[10],"they":[11],"often":[12],"fall":[13],"short":[14],"in":[15,26,159],"either":[16],"oversimplifying":[17],"pairwise":[18],"relationships":[19],"or":[20],"struggling":[21],"with":[22,61,143],"inefficient":[23],"decompositions":[25],"high-dimensional":[27],"Euclidean":[28,83],"spaces.":[29],"In":[30,82],"this":[31,100],"paper,":[32],"we":[33,56,98,111,131],"introduce":[34],"a":[35],"novel":[36],"approach":[37],"that":[38,153],"begins":[39],"to":[40,119,165],"generate":[41],"hypergraphs":[42],"by":[43],"leveraging":[44],"sparse":[45],"representation":[46],"learning":[47],"from":[48],"data":[49],"points.":[50],"Based":[51],"on":[52,106,134],"the":[53,86,107,121,125,128,157],"generated":[54],"hypergraph,":[55],"propose":[57],"an":[58,103,113],"optimization":[59,88,117],"function":[60],"orthogonality":[62],"constraints":[63],"for":[64,73],"hypergraph":[66],"clustering,":[68],"which":[69],"incorporates":[70],"each":[74],"view":[75],"and":[76,94,139,169],"ensures":[77],"consistency":[78],"across":[79],"different":[80],"views.":[81],"space,":[84],"solving":[85],"orthogonality-constrained":[87],"problem":[89,101],"may":[90],"yield":[91],"local":[92],"maxima":[93],"approximation":[95],"errors.":[96],"Innovately,":[97],"transform":[99],"into":[102],"unconstrained":[104],"form":[105],"Grassmannian":[108],"manifold.":[109],"Finally,":[110],"devise":[112],"alternating":[114],"iterative":[115],"Riemannian":[116],"algorithm":[118],"solve":[120],"problem.":[122],"To":[123],"validate":[124],"effectiveness":[126],"of":[127,161],"proposed":[129],"algorithm,":[130],"test":[132],"it":[133],"four":[135],"real-world":[136],"datasets":[138],"compare":[140],"its":[141,166],"performance":[142,163],"six":[144],"state-of-the-art":[145],"algorithms.":[148],"The":[149],"experimental":[150],"results":[151],"demonstrate":[152],"our":[154],"method":[155],"outperforms":[156],"baselines":[158],"terms":[160],"due":[164],"superior":[167],"low-dimensional":[168],"resilient":[170],"feature":[171],"representation.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
