{"id":"https://openalex.org/W2970503027","doi":"https://doi.org/10.1109/tnnls.2019.2933223","title":"Semi-Supervised Non-Negative Matrix Factorization With Dissimilarity and Similarity Regularization","display_name":"Semi-Supervised Non-Negative Matrix Factorization With Dissimilarity and Similarity Regularization","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2970503027","doi":"https://doi.org/10.1109/tnnls.2019.2933223","mag":"2970503027","pmid":"https://pubmed.ncbi.nlm.nih.gov/31484134"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2019.2933223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2933223","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/A5013880628","display_name":"Yuheng Jia","orcid":"https://orcid.org/0000-0002-3907-6550"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Yuheng Jia","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008386708","display_name":"Sam Kwong","orcid":"https://orcid.org/0000-0001-7484-7261"},"institutions":[{"id":"https://openalex.org/I4210105229","display_name":"City University of Hong Kong, Shenzhen Research Institute","ror":"https://ror.org/00xc0ma20","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210105229"]},{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Sam Kwong","raw_affiliation_strings":["City University of Hong Kong Shenzhen Research Institute, Shenzhen, China","Department of Computer Science, City University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"City University of Hong Kong Shenzhen Research Institute, Shenzhen, China","institution_ids":["https://openalex.org/I168719708","https://openalex.org/I4210105229"]},{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031957432","display_name":"Junhui Hou","orcid":"https://orcid.org/0000-0003-3431-2021"},"institutions":[{"id":"https://openalex.org/I4210105229","display_name":"City University of Hong Kong, Shenzhen Research Institute","ror":"https://ror.org/00xc0ma20","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210105229"]},{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Junhui Hou","raw_affiliation_strings":["City University of Hong Kong Shenzhen Research Institute, Shenzhen, China","Department of Computer Science, City University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"City University of Hong Kong Shenzhen Research Institute, Shenzhen, China","institution_ids":["https://openalex.org/I168719708","https://openalex.org/I4210105229"]},{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081114494","display_name":"Wenhui Wu","orcid":"https://orcid.org/0000-0002-0416-7719"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wenhui Wu","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5013880628"],"corresponding_institution_ids":["https://openalex.org/I168719708"],"apc_list":null,"apc_paid":null,"fwci":5.4661,"has_fulltext":false,"cited_by_count":90,"citation_normalized_percentile":{"value":0.96663206,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"31","issue":"7","first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9983000159263611,"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":0.9983000159263611,"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":0.9682999849319458,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9652000069618225,"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/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.8911334276199341},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.690829873085022},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6596882343292236},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6174349188804626},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5989060997962952},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5751383304595947},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5433865189552307},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5116655826568604},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48674893379211426},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.46009084582328796},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.4167421758174896},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3994203805923462},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36886006593704224},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32114994525909424},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14789700508117676},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.08696386218070984}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.8911334276199341},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.690829873085022},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6596882343292236},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6174349188804626},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5989060997962952},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5751383304595947},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5433865189552307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5116655826568604},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48674893379211426},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.46009084582328796},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.4167421758174896},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3994203805923462},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36886006593704224},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32114994525909424},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14789700508117676},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.08696386218070984},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2019.2933223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2933223","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:31484134","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31484134","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":[{"display_name":"Reduced inequalities","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G4835894923","display_name":null,"funder_award_id":"61772344","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7678096932","display_name":null,"funder_award_id":"61672443","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7867221944","display_name":null,"funder_award_id":"61871342","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":56,"referenced_works":["https://openalex.org/W206759535","https://openalex.org/W1084418525","https://openalex.org/W1489499640","https://openalex.org/W1504886279","https://openalex.org/W1609068386","https://openalex.org/W1854811422","https://openalex.org/W1902027874","https://openalex.org/W1968970305","https://openalex.org/W1983069960","https://openalex.org/W2000355138","https://openalex.org/W2002469984","https://openalex.org/W2013029404","https://openalex.org/W2019247858","https://openalex.org/W2029728040","https://openalex.org/W2043545458","https://openalex.org/W2052478943","https://openalex.org/W2063069198","https://openalex.org/W2063790512","https://openalex.org/W2067931421","https://openalex.org/W2077583079","https://openalex.org/W2081117716","https://openalex.org/W2088857627","https://openalex.org/W2101139104","https://openalex.org/W2104819583","https://openalex.org/W2108119513","https://openalex.org/W2108919995","https://openalex.org/W2118718620","https://openalex.org/W2132914434","https://openalex.org/W2135029798","https://openalex.org/W2149532724","https://openalex.org/W2158842967","https://openalex.org/W2167686991","https://openalex.org/W2168103112","https://openalex.org/W2234634182","https://openalex.org/W2291338622","https://openalex.org/W2405409114","https://openalex.org/W2482276862","https://openalex.org/W2571268788","https://openalex.org/W2591838227","https://openalex.org/W2607323999","https://openalex.org/W2691337902","https://openalex.org/W2749035964","https://openalex.org/W2782630728","https://openalex.org/W2784309606","https://openalex.org/W2804454015","https://openalex.org/W2898080674","https://openalex.org/W2923396414","https://openalex.org/W3143596294","https://openalex.org/W4295235562","https://openalex.org/W6639041367","https://openalex.org/W6674848643","https://openalex.org/W6677759377","https://openalex.org/W6680012447","https://openalex.org/W6721880745","https://openalex.org/W6734173446","https://openalex.org/W6740457415"],"related_works":["https://openalex.org/W2127243424","https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W34555840"],"abstract_inverted_index":{"In":[0],"this":[1],"article,":[2],"we":[3,104],"propose":[4],"a":[5,35,77,89,114,140],"semi-supervised":[6],"non-negative":[7],"matrix":[8],"factorization":[9],"(NMF)":[10],"model":[11,22,85,133],"by":[12],"means":[13],"of":[14,25,37,65,69,80],"elegantly":[15],"modeling":[16],"the":[17,48,53,61,66,108,119,131,135,149],"label":[18],"information.":[19],"The":[20,83],"proposed":[21,84,109,132],"is":[23,45,86],"capable":[24],"generating":[26],"discriminable":[27],"low-dimensional":[28,67],"representations":[29,68],"to":[30,51,113,139,153],"improve":[31],"clustering":[32,150],"performance.":[33],"Specifically,":[34],"pair":[36],"complementary":[38],"regularizers,":[39,44],"i.e.,":[40,148],"similarity":[41,62],"and":[42,63,94],"dissimilarity":[43,64],"incorporated":[46],"into":[47],"conventional":[49],"NMF":[50,137],"guide":[52],"factorization.":[54],"And,":[55],"they":[56],"impose":[57],"restrictions":[58],"on":[59],"both":[60],"data":[70,146],"samples":[71],"with":[72,97],"labels":[73],"as":[74,76,88,124,126],"well":[75,125],"small":[78],"number":[79],"unlabeled":[81],"ones.":[82],"formulated":[87],"well-posed":[90],"constrained":[91],"optimization":[92],"problem":[93],"further":[95],"solved":[96],"an":[98],"efficient":[99],"alternating":[100],"iterative":[101],"algorithm.":[102],"Moreover,":[103],"theoretically":[105],"prove":[106],"that":[107,117,130],"algorithm":[110],"can":[111],"converge":[112],"limiting":[115],"point":[116],"meets":[118],"Karush-Kuhn-Tucker":[120],"conditions.":[121],"Extensive":[122],"experiments":[123],"comprehensive":[127],"analysis":[128],"demonstrate":[129],"outperforms":[134],"state-of-the-art":[136],"methods":[138],"large":[141],"extent":[142],"over":[143],"five":[144],"benchmark":[145],"sets,":[147],"accuracy":[151],"increases":[152],"82.2%":[154],"from":[155],"57.0%.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
