{"id":"https://openalex.org/W4361284154","doi":"https://doi.org/10.3390/info14040208","title":"Adaptive Kernel Graph Nonnegative Matrix Factorization","display_name":"Adaptive Kernel Graph Nonnegative Matrix Factorization","publication_year":2023,"publication_date":"2023-03-29","ids":{"openalex":"https://openalex.org/W4361284154","doi":"https://doi.org/10.3390/info14040208"},"language":"en","primary_location":{"id":"doi:10.3390/info14040208","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info14040208","pdf_url":"https://www.mdpi.com/2078-2489/14/4/208/pdf?version=1680073562","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/14/4/208/pdf?version=1680073562","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028104367","display_name":"Rui-Yu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui-Yu Li","raw_affiliation_strings":["School of Software, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"],"raw_orcid":"https://orcid.org/0000-0002-8122-4254","affiliations":[{"raw_affiliation_string":"School of Software, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101652862","display_name":"Yu Guo","orcid":"https://orcid.org/0000-0002-5489-8288"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Guo","raw_affiliation_strings":["School of Software, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"],"raw_orcid":"https://orcid.org/0000-0002-5489-8288","affiliations":[{"raw_affiliation_string":"School of Software, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101775575","display_name":"Bin Zhang","orcid":"https://orcid.org/0000-0002-4936-0061"},"institutions":[{"id":"https://openalex.org/I7726996","display_name":"Henan University of Economic and Law","ror":"https://ror.org/000jtc944","country_code":"CN","type":"education","lineage":["https://openalex.org/I7726996"]},{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bin Zhang","raw_affiliation_strings":["School of Software, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China","Zhengzhou Key Laboratory of Intelligent Assembly Manufacturing and Logistics Optimization, Zhengzhou College of Finance and Economics, Zhengzhou 450053, China"],"raw_orcid":"https://orcid.org/0000-0002-4936-0061","affiliations":[{"raw_affiliation_string":"School of Software, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Zhengzhou Key Laboratory of Intelligent Assembly Manufacturing and Logistics Optimization, Zhengzhou College of Finance and Economics, Zhengzhou 450053, China","institution_ids":["https://openalex.org/I7726996"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101775575"],"corresponding_institution_ids":["https://openalex.org/I7726996","https://openalex.org/I87445476"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1779},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1779},"fwci":0.2858,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.48682508,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"14","issue":"4","first_page":"208","last_page":"208"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9969000220298767,"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":0.9969000220298767,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9793000221252441,"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"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9343000054359436,"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/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.6744325160980225},{"id":"https://openalex.org/keywords/graph-kernel","display_name":"Graph kernel","score":0.5932314395904541},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5910122394561768},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5065621137619019},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49834227561950684},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49182724952697754},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.47308045625686646},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.45581573247909546},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4557400345802307},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4467047154903412},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4190790355205536},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4067211449146271},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40572234988212585},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34677112102508545},{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.33036065101623535},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.3019736111164093},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2503242492675781},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.09736242890357971},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.09596845507621765},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.09437936544418335}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.6744325160980225},{"id":"https://openalex.org/C100595998","wikidata":"https://www.wikidata.org/wiki/Q11731931","display_name":"Graph kernel","level":5,"score":0.5932314395904541},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5910122394561768},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5065621137619019},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49834227561950684},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49182724952697754},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.47308045625686646},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.45581573247909546},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4557400345802307},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4467047154903412},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4190790355205536},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4067211449146271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40572234988212585},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34677112102508545},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.33036065101623535},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.3019736111164093},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2503242492675781},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.09736242890357971},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.09596845507621765},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.09437936544418335},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info14040208","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info14040208","pdf_url":"https://www.mdpi.com/2078-2489/14/4/208/pdf?version=1680073562","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:dd1834b0cf7f4ef79c92e399cebd8e6d","is_oa":true,"landing_page_url":"https://doaj.org/article/dd1834b0cf7f4ef79c92e399cebd8e6d","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":"Information, Vol 14, Iss 4, p 208 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info14040208","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info14040208","pdf_url":"https://www.mdpi.com/2078-2489/14/4/208/pdf?version=1680073562","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4361284154.pdf"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W18701524","https://openalex.org/W1902027874","https://openalex.org/W1972908405","https://openalex.org/W1974451338","https://openalex.org/W1979089718","https://openalex.org/W1989637899","https://openalex.org/W2053566983","https://openalex.org/W2059745395","https://openalex.org/W2076583508","https://openalex.org/W2078455576","https://openalex.org/W2097308346","https://openalex.org/W2108119513","https://openalex.org/W2112104211","https://openalex.org/W2114508388","https://openalex.org/W2121196976","https://openalex.org/W2123649031","https://openalex.org/W2123921160","https://openalex.org/W2126185804","https://openalex.org/W2127218421","https://openalex.org/W2136635436","https://openalex.org/W2138451337","https://openalex.org/W2154872931","https://openalex.org/W2168103112","https://openalex.org/W2364980675","https://openalex.org/W2406581873","https://openalex.org/W2494395359","https://openalex.org/W2735766746","https://openalex.org/W2740503509","https://openalex.org/W2758049963","https://openalex.org/W2765158981","https://openalex.org/W2904176920","https://openalex.org/W2909324822","https://openalex.org/W2936483426","https://openalex.org/W2962805032","https://openalex.org/W2963051348","https://openalex.org/W2965052154","https://openalex.org/W2993529567","https://openalex.org/W2997701990","https://openalex.org/W3025752507","https://openalex.org/W3212172675","https://openalex.org/W4250589301","https://openalex.org/W4251670979","https://openalex.org/W4282835295","https://openalex.org/W4303856968","https://openalex.org/W4310991244","https://openalex.org/W6643675208","https://openalex.org/W6675747103","https://openalex.org/W6676321539","https://openalex.org/W6677171112","https://openalex.org/W6678914141","https://openalex.org/W6680012447","https://openalex.org/W6682644385","https://openalex.org/W6685529966"],"related_works":["https://openalex.org/W1984421104","https://openalex.org/W2512565647","https://openalex.org/W2001772920","https://openalex.org/W2393746448","https://openalex.org/W2905418897","https://openalex.org/W1985034083","https://openalex.org/W3093470103","https://openalex.org/W2398887903","https://openalex.org/W2534878021","https://openalex.org/W1998640076"],"abstract_inverted_index":{"Nonnegative":[0],"matrix":[1,50,96,138],"factorization":[2,97,161],"(NMF)":[3],"is":[4,55,133,145],"an":[5,117,175],"efficient":[6,176],"method":[7,87,156],"for":[8],"feature":[9,113,151,171],"learning":[10,16,132],"in":[11,58,88,127,185,190,221],"the":[12,22,47,52,59,68,104,108,111,137,149,160,167,186,194,199,205,217,242,245],"field":[13],"of":[14,25,51,62,107,201,219],"machine":[15],"and":[17,30,64,166,229,241,251],"data":[18,63,109],"mining.":[19],"To":[20,76],"investigate":[21],"nonlinear":[23,112,206],"characteristics":[24],"datasets,":[26],"kernel-method-based":[27],"NMF":[28],"(KNMF)":[29],"its":[31],"graph-regularized":[32],"extensions":[33],"have":[34],"received":[35],"much":[36],"attention":[37],"from":[38],"various":[39,238],"researchers":[40],"due":[41],"to":[42,73,101,181,203],"their":[43],"promising":[44],"performance.":[45],"However,":[46],"graph":[48,94,131,143],"similarity":[49,119,130],"existing":[53],"methods":[54,240],"often":[56],"predefined":[57],"original":[60],"space":[61],"kept":[65],"unchanged":[66],"during":[67],"matrix-factorization":[69,86],"procedure,":[70],"which":[71,128],"leads":[72],"non-optimal":[74],"graphs.":[75],"address":[77],"these":[78],"problems,":[79],"we":[80],"propose":[81],"a":[82,123],"kernel-graph-learning-based,":[83],"nonlinear,":[84],"nonnegative":[85,95],"this":[89],"paper,":[90],"termed":[91],"adaptive":[92,118],"kernel":[93],"(AKGNMF).":[98],"In":[99,173],"order":[100],"automatically":[102],"capture":[103],"manifold":[105],"structure":[106,165],"on":[110,148,158,193,213],"space,":[114],"AKGNMF":[115,202,220,247],"learned":[116,150],"graph.":[120],"We":[121],"formulated":[122],"unified":[124],"objective":[125,188],"function,":[126],"global":[129],"optimized":[134],"jointly":[135],"with":[136,208,237],"decomposition":[139],"process.":[140],"A":[141],"local":[142],"Laplacian":[144],"further":[146],"imposed":[147],"subspace":[152,170],"representation.":[153],"The":[154],"proposed":[155,246],"relies":[157],"both":[159],"that":[162],"respects":[163],"geometric":[164],"mapped":[168],"high-dimensional":[169],"representations.":[172],"addition,":[174],"iterative":[177],"solution":[178],"was":[179],"derived":[180],"update":[182],"all":[183],"variables":[184],"resultant":[187],"problem":[189],"turn.":[191],"Experiments":[192,212],"synthetic":[195],"dataset":[196,207],"visually":[197],"demonstrate":[198],"ability":[200],"separate":[204],"high":[209],"clustering":[210,225],"accuracy.":[211],"real-world":[214],"datasets":[215],"verified":[216],"effectiveness":[218,250],"three":[222],"aspects,":[223],"including":[224],"performance,":[226],"parameter":[227],"sensitivity":[228],"convergence.":[230],"Comprehensive":[231],"experimental":[232],"findings":[233],"indicate":[234],"that,":[235],"compared":[236],"classic":[239],"state-of-the-art":[243],"methods,":[244],"algorithm":[248],"demonstrated":[249],"superiority.":[252]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2023-03-31T00:00:00"}