{"id":"https://openalex.org/W4416252411","doi":"https://doi.org/10.1109/access.2025.3630750","title":"Non-Negative Matrix Factorization in Recommender Models: Concept, Survey, and Future Direction","display_name":"Non-Negative Matrix Factorization in Recommender Models: Concept, Survey, and Future Direction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416252411","doi":"https://doi.org/10.1109/access.2025.3630750"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3630750","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3630750","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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://doi.org/10.1109/access.2025.3630750","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102819300","display_name":"Rachana Mehta","orcid":"https://orcid.org/0000-0001-9683-6643"},"institutions":[{"id":"https://openalex.org/I33586908","display_name":"Pandit Deendayal Energy University","ror":"https://ror.org/02nsv5p42","country_code":"IN","type":"education","lineage":["https://openalex.org/I33586908"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rachana Mehta","raw_affiliation_strings":["Computer Science and Engineering Department, School of Technology, Pandit Deendayal Energy University, Gandhinagar, India"],"raw_orcid":"https://orcid.org/0000-0001-9683-6643","affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, School of Technology, Pandit Deendayal Energy University, Gandhinagar, India","institution_ids":["https://openalex.org/I33586908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072010475","display_name":"Shakti Mishra","orcid":"https://orcid.org/0000-0002-5961-3114"},"institutions":[{"id":"https://openalex.org/I33586908","display_name":"Pandit Deendayal Energy University","ror":"https://ror.org/02nsv5p42","country_code":"IN","type":"education","lineage":["https://openalex.org/I33586908"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shakti Mishra","raw_affiliation_strings":["Computer Science and Engineering Department, School of Technology, Pandit Deendayal Energy University, Gandhinagar, India"],"raw_orcid":"https://orcid.org/0000-0002-5961-3114","affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, School of Technology, Pandit Deendayal Energy University, Gandhinagar, India","institution_ids":["https://openalex.org/I33586908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066292961","display_name":"Snehanshu Saha","orcid":"https://orcid.org/0000-0002-8458-604X"},"institutions":[{"id":"https://openalex.org/I4210148827","display_name":"Birla Institute of Technology and Science, Pilani - Goa Campus","ror":"https://ror.org/046sh6j17","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210148827","https://openalex.org/I74796645"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Snehanshu Saha","raw_affiliation_strings":["Department of Computer Science and Information Systems, APPCAIR, BITS Pilani K K Birla Goa Campus, Goa, India"],"raw_orcid":"https://orcid.org/0000-0002-8458-604X","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Systems, APPCAIR, BITS Pilani K K Birla Goa Campus, Goa, India","institution_ids":["https://openalex.org/I4210148827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.3589,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92240503,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"13","issue":null,"first_page":"192492","last_page":"192517"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.864799976348877,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.864799976348877,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T14413","display_name":"Advanced Technologies in Various Fields","score":0.014299999922513962,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.012299999594688416,"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/recommender-system","display_name":"Recommender system","score":0.8805999755859375},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.7972000241279602},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.7516999840736389},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.7233999967575073},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.6532999873161316},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.4925000071525574},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.4449999928474426},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.43479999899864197}],"concepts":[{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8805999755859375},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.7972000241279602},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7929999828338623},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.7516999840736389},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.7233999967575073},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.6532999873161316},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4925000071525574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4659000039100647},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.4449999928474426},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.43479999899864197},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4309000074863434},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3937999904155731},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3815000057220459},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3617999851703644},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.35670000314712524},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.26330000162124634},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.2567000091075897}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3630750","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3630750","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0a77a7c40a9b451786b0912a264511ba","is_oa":true,"landing_page_url":"https://doaj.org/article/0a77a7c40a9b451786b0912a264511ba","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 13, Pp 192492-192517 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3630750","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3630750","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recommender":[0],"Systems":[1],"have":[2,115,167],"gained":[3],"attraction":[4],"since":[5],"last":[6],"two":[7],"decades":[8],"owing":[9],"to":[10,37,54,95,114,123,146,162,172,185],"its":[11,66],"popularity":[12],"of":[13,19,72,98,104,125,136,175,275,303,329],"providing":[14],"customers":[15],"with":[16,190,208,226,288,306],"the":[17,51,73,96,119,143,219,247,270,279,312,327],"information":[18,236],"their":[20,229],"choice,":[21],"items":[22],"they":[23,27,237],"might":[24,28],"purchase,":[25],"movies":[26],"watch":[29],"and":[30,42,56,65,92,213,232,241,263,273,290],"many":[31],"preferences.":[32],"This":[33,121,216],"has":[34,49,154],"led":[35],"recommenders":[36,55,304],"penetrate":[38],"almost":[39],"all":[40],"e-commerce":[41],"industrial":[43],"applications.":[44],"The":[45,133,244,265,294,309],"Netflix":[46],"Prize":[47],"competition":[48],"shown":[50],"rising":[52],"path":[53],"Singular":[57],"Value":[58],"Decomposition":[59],"(SVD)":[60],"based":[61,200,223,234,249,252],"factorization":[62,126],"techniques.":[63],"SVD":[64,87,289],"variants":[67],"are":[68],"considered":[69],"as":[70,184],"one":[71,323],"efficient":[74],"approach":[75],"for":[76,81,149,331],"recommendation":[77],"task,":[78],"especially":[79],"aligned":[80],"collaborative":[82],"filtering":[83],"task.":[84],"However,":[85,177],"these":[86],"approaches":[88,255],"remains":[89],"less":[90],"interpretable":[91,151],"explainable,":[93],"due":[94],"presence":[97],"negative":[99,116],"components":[100,117,131],"in":[101,118,206,318],"latent":[102],"features":[103],"entities.":[105],"In":[106],"a":[107],"realistic":[108],"scenario,":[109],"it":[110],"is":[111],"not":[112],"possible":[113],"features.":[120],"leads":[122],"exploration":[124],"techniques":[127],"focused":[128],"on":[129,198,221,228,235,253,285,299],"positive":[130],"only.":[132],"non-negative":[134],"counterpart":[135],"SVD,":[137],"Non-negative":[138],"Matrix":[139],"Factorization":[140],"(NMF)":[141],"imposes":[142],"non-negativity":[144],"constraint":[145],"features,":[147],"allowing":[148],"more":[150],"results.":[152],"It":[153],"wide":[155],"applicability":[156],"ranging":[157],"from":[158],"Bioinformatics,":[159],"topic":[160],"modeling":[161,231],"recommenders.":[163,319,332],"Till":[164],"date,":[165],"there":[166,178],"been":[168],"several":[169],"survey":[170,197],"dedicated":[171],"core":[173],"working":[174],"NMF.":[176],"was":[179,194,297],"very":[180],"limited":[181],"literature":[182],"available":[183],"how":[186],"different":[187],"NMF":[188,199,205,222,248,276,286,317,330],"works":[189],"recommender":[191,201,224,250],"systems.":[192],"There":[193],"no":[195],"streamlined":[196],"models":[202,225,287],"that":[203],"explores":[204],"depth":[207],"advanced":[209],"domains,":[210],"case":[211],"study":[212],"future":[214],"directions.":[215],"article":[217,245,266,280],"presents":[218],"insight":[220],"focus":[227],"mathematical":[230],"taxonomy":[233],"use,":[238],"penalization":[239],"term":[240],"optimization":[242],"approach.":[243],"offers":[246],"model":[251],"emerging":[254],"like":[256],"Deep":[257],"Learning,":[258,260],"Federated":[259],"Transformers,":[261],"Explainability":[262],"Dynamicity.":[264],"also":[267],"brings":[268],"up":[269],"open":[271],"issues":[272],"challenges":[274],"models.":[277],"Further,":[278],"presented":[281],"an":[282],"experimental":[283,295],"analysis":[284,296],"Neural":[291],"Network":[292],"model.":[293],"covered":[298],"three":[300],"benchmarked":[301],"datasets":[302],"along":[305],"stability":[307],"analysis.":[308],"results":[310],"showcased":[311],"performance":[313],"improvement":[314],"brought":[315],"by":[316],"Through":[320],"this":[321],"article,":[322],"can":[324],"plunge":[325],"into":[326],"dynamics":[328]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-10T00:00:00"}