{"id":"https://openalex.org/W4383890347","doi":"https://doi.org/10.1109/tnnls.2023.3288769","title":"Uncertainty-Adjusted Recommendation via Matrix Factorization With Weighted Losses","display_name":"Uncertainty-Adjusted Recommendation via Matrix Factorization With Weighted Losses","publication_year":2023,"publication_date":"2023-07-11","ids":{"openalex":"https://openalex.org/W4383890347","doi":"https://doi.org/10.1109/tnnls.2023.3288769","pmid":"https://pubmed.ncbi.nlm.nih.gov/37432811"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3288769","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3288769","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/A5062633566","display_name":"Rodrigo Alves","orcid":"https://orcid.org/0000-0001-7458-5281"},"institutions":[{"id":"https://openalex.org/I44504214","display_name":"Czech Technical University in Prague","ror":"https://ror.org/03kqpb082","country_code":"CZ","type":"education","lineage":["https://openalex.org/I44504214"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Rodrigo Alves","raw_affiliation_strings":["Department of Applied Mathematics, Czech Technical University in Prague (CTU), Prague, Czech Republic Prague"],"raw_orcid":"https://orcid.org/0000-0001-7458-5281","affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics, Czech Technical University in Prague (CTU), Prague, Czech Republic Prague","institution_ids":["https://openalex.org/I44504214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018822505","display_name":"Antoine Ledent","orcid":"https://orcid.org/0000-0001-8440-2784"},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Antoine Ledent","raw_affiliation_strings":["School of Computing and Information Sciences (SCIS), Singapore Management University (SMU), Bras Basah, Singapore","School of Computing and Information Sciences (SCIS), Singapore Management University (SMU), Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-8440-2784","affiliations":[{"raw_affiliation_string":"School of Computing and Information Sciences (SCIS), Singapore Management University (SMU), Bras Basah, Singapore","institution_ids":["https://openalex.org/I79891267"]},{"raw_affiliation_string":"School of Computing and Information Sciences (SCIS), Singapore Management University (SMU), Singapore, Singapore","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091841504","display_name":"Marius Kloft","orcid":"https://orcid.org/0000-0001-6829-3725"},"institutions":[{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]},{"id":"https://openalex.org/I2802076133","display_name":"University of Koblenz and Landau","ror":"https://ror.org/01j9f6752","country_code":"DE","type":"education","lineage":["https://openalex.org/I2802076133"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marius Kloft","raw_affiliation_strings":["Department of Computer Science, University of Kaiserslautern-Landau (RPTU), Kaiserslautern, Germany"],"raw_orcid":"https://orcid.org/0000-0001-6829-3725","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Kaiserslautern-Landau (RPTU), Kaiserslautern, Germany","institution_ids":["https://openalex.org/I2802076133","https://openalex.org/I153267046"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9035,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.87896227,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"35","issue":"11","first_page":"15624","last_page":"15637"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.996399998664856,"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"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.996399998664856,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9945999979972839,"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/T10057","display_name":"Face and Expression Recognition","score":0.9850000143051147,"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/weighting","display_name":"Weighting","score":0.7180484533309937},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6781806349754333},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6511819958686829},{"id":"https://openalex.org/keywords/rss","display_name":"RSS","score":0.5843608379364014},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5801683068275452},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.568189799785614},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5087979435920715},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.47247716784477234},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.4532701373100281},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4122255742549896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3677358031272888},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29808756709098816}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7180484533309937},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6781806349754333},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6511819958686829},{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.5843608379364014},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5801683068275452},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.568189799785614},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5087979435920715},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.47247716784477234},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4532701373100281},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4122255742549896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3677358031272888},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29808756709098816},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2023.3288769","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3288769","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:37432811","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37432811","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},{"id":"pmh:oai:ink.library.smu.edu.sg:sis_research-9034","is_oa":false,"landing_page_url":"https://ink.library.smu.edu.sg/sis_research/8031","pdf_url":null,"source":{"id":"https://openalex.org/S4306401925","display_name":"Singapore Management University Institutional Knowledge (InK) (Singapore Management University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79891267","host_organization_name":"Singapore Management University","host_organization_lineage":["https://openalex.org/I79891267"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://doi.org/10.1109/TNNLS.2023.3288769","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Responsible consumption and production","id":"https://metadata.un.org/sdg/12","score":0.44999998807907104}],"awards":[{"id":"https://openalex.org/G1332273124","display_name":null,"funder_award_id":"KL 2698/2-1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G3336781480","display_name":null,"funder_award_id":"KL 2698/6-1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G4853260319","display_name":null,"funder_award_id":"KL 2698/7-1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G486260054","display_name":null,"funder_award_id":"S21010C","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"},{"id":"https://openalex.org/G5376319505","display_name":null,"funder_award_id":"B0770E","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"},{"id":"https://openalex.org/G8730200936","display_name":null,"funder_award_id":"KL 2698/5-1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W1977290284","https://openalex.org/W1996336859","https://openalex.org/W1998635907","https://openalex.org/W2030161963","https://openalex.org/W2043150617","https://openalex.org/W2047071281","https://openalex.org/W2054141820","https://openalex.org/W2070689335","https://openalex.org/W2107411554","https://openalex.org/W2116354394","https://openalex.org/W2119523409","https://openalex.org/W2134332047","https://openalex.org/W2172985765","https://openalex.org/W2248352351","https://openalex.org/W2408727916","https://openalex.org/W2542250862","https://openalex.org/W2775111227","https://openalex.org/W2910257236","https://openalex.org/W2913415152","https://openalex.org/W2957946950","https://openalex.org/W2962904925","https://openalex.org/W2987679642","https://openalex.org/W2993432425","https://openalex.org/W3014765163","https://openalex.org/W3024536663","https://openalex.org/W3033630125","https://openalex.org/W3094857757","https://openalex.org/W3123160711","https://openalex.org/W3153539640","https://openalex.org/W3171860698","https://openalex.org/W3176420923","https://openalex.org/W4211243454","https://openalex.org/W4220748984","https://openalex.org/W4248672808","https://openalex.org/W4250954493","https://openalex.org/W4301425558","https://openalex.org/W4306830375","https://openalex.org/W4307779123","https://openalex.org/W4323527069","https://openalex.org/W4323527093","https://openalex.org/W6639038035","https://openalex.org/W6641162989","https://openalex.org/W6675683289","https://openalex.org/W6675902009","https://openalex.org/W6677434587","https://openalex.org/W6677872535","https://openalex.org/W6677959539","https://openalex.org/W6680702173","https://openalex.org/W6682042988","https://openalex.org/W6683370129","https://openalex.org/W6697077597","https://openalex.org/W6730063867","https://openalex.org/W6735443497","https://openalex.org/W6749925554","https://openalex.org/W6758841232","https://openalex.org/W6768381419","https://openalex.org/W6795567358","https://openalex.org/W6796813622","https://openalex.org/W6803932303","https://openalex.org/W6839747180","https://openalex.org/W6849473202"],"related_works":["https://openalex.org/W426968574","https://openalex.org/W2365639220","https://openalex.org/W2382520895","https://openalex.org/W2393709043","https://openalex.org/W3177075132","https://openalex.org/W2963185427","https://openalex.org/W2065296176","https://openalex.org/W1973739845","https://openalex.org/W119752240","https://openalex.org/W2201180357"],"abstract_inverted_index":{"In":[0,44],"a":[1,49,74,105],"recommender":[2],"systems":[3],"(RSs)":[4],"dataset,":[5],"observed":[6],"ratings":[7,25],"are":[8],"subject":[9,85],"to":[10,81,86,95,160],"unequal":[11],"amounts":[12,88],"of":[13,62,65,68,89,136,182],"noise.":[14],"Some":[15,33],"users":[16],"might":[17],"be":[18,36,82],"consistently":[19],"more":[20,79,93],"conscientious":[21],"in":[22,59,108,127,165,180],"choosing":[23],"the":[24,29,60,66,97,109,115,137,143,153,192],"they":[26,31],"provide":[27],"for":[28],"content":[30],"consume.":[32],"items":[34],"may":[35],"very":[37],"divisive":[38],"and":[39,91,118,176],"elicit":[40],"highly":[41],"noisy":[42],"reviews.":[43],"this":[45,128],"article,":[46],"we":[47,111,131,188],"perform":[48],"nuclear-norm-based":[50],"matrix":[51,166],"factorization":[52],"method":[53,169],"which":[54,141,157],"relies":[55],"on":[56,173],"side":[57],"information":[58,194],"form":[61],"an":[63,133],"estimate":[64,101],"uncertainty":[67,76,100],"each":[69],"rating.":[70],"A":[71],"rating":[72],"with":[73,122],"higher":[75],"is":[77,102,150],"considered":[78],"likely":[80,94],"erroneous":[83],"or":[84],"large":[87],"noise,":[90],"therefore":[92],"mislead":[96],"model.":[98],"Our":[99,168],"used":[103,191],"as":[104],"weighting":[106],"factor":[107],"loss":[110],"optimize.":[112],"To":[113],"maintain":[114],"favorable":[116],"scaling":[117],"theoretical":[119],"guarantees":[120],"coming":[121],"nuclear":[123],"norm":[124,139,156],"regularization":[125,148],"even":[126],"weighted":[129,154],"context,":[130],"introduce":[132],"adjusted":[134],"version":[135],"trace":[138,155],"regularizer":[140],"takes":[142],"weights":[144],"into":[145],"account.":[146],"This":[147],"strategy":[149],"inspired":[151],"from":[152],"was":[158],"introduced":[159],"tackle":[161],"nonuniform":[162],"sampling":[163],"regimes":[164],"completion.":[167],"exhibits":[170],"state-of-the-art":[171],"performance":[172,184],"both":[174],"synthetic":[175],"real":[177],"life":[178],"datasets":[179],"terms":[181],"various":[183],"measures,":[185],"confirming":[186],"that":[187],"have":[189],"successfully":[190],"auxiliary":[193],"extracted.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
