{"id":"https://openalex.org/W2140065105","doi":"https://doi.org/10.1109/tasl.2010.2040784","title":"Non-Negative Tensor Factorization Applied to Music Genre Classification","display_name":"Non-Negative Tensor Factorization Applied to Music Genre Classification","publication_year":2010,"publication_date":"2010-01-22","ids":{"openalex":"https://openalex.org/W2140065105","doi":"https://doi.org/10.1109/tasl.2010.2040784","mag":"2140065105"},"language":"en","primary_location":{"id":"doi:10.1109/tasl.2010.2040784","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2010.2040784","pdf_url":null,"source":{"id":"https://openalex.org/S199497470","display_name":"IEEE Transactions on Audio Speech and Language Processing","issn_l":"1558-7916","issn":["1558-7916","1558-7924"],"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 Audio, Speech, and Language Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"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/A5084672392","display_name":"Emmanouil Benetos","orcid":null},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]},{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB","GR"],"is_corresponding":true,"raw_author_name":"E Benetos","raw_affiliation_strings":["Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece","School of Electronic Engineering and Computer Science, Queen''s Mary, University of London, London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]},{"raw_affiliation_string":"School of Electronic Engineering and Computer Science, Queen''s Mary, University of London, London, UK","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065184406","display_name":"Constantine Kotropoulos","orcid":"https://orcid.org/0000-0001-9939-7930"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"C Kotropoulos","raw_affiliation_strings":["Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5084672392"],"corresponding_institution_ids":["https://openalex.org/I166337079","https://openalex.org/I21370196"],"apc_list":null,"apc_paid":null,"fwci":5.075,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.95999492,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"18","issue":"8","first_page":"1955","last_page":"1967"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11309","display_name":"Music and Audio Processing","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10788","display_name":"Neuroscience and Music Perception","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6936713457107544},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6414203643798828},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6323080658912659},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5635046362876892},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.558407187461853},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4718087911605835},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.46838170289993286},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3204266130924225}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6936713457107544},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6414203643798828},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6323080658912659},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5635046362876892},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.558407187461853},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4718087911605835},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.46838170289993286},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3204266130924225},{"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},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tasl.2010.2040784","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2010.2040784","pdf_url":null,"source":{"id":"https://openalex.org/S199497470","display_name":"IEEE Transactions on Audio Speech and Language Processing","issn_l":"1558-7916","issn":["1558-7916","1558-7924"],"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 Audio, Speech, and Language Processing","raw_type":"journal-article"},{"id":"pmh:oai:openaccess.city.ac.uk:2048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2010.2040784>","pdf_url":null,"source":{"id":"https://openalex.org/S4306401940","display_name":"City Research Online (City University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I180825142","host_organization_name":"City, University of London","host_organization_lineage":["https://openalex.org/I180825142"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.474.9358","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.474.9358","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://poseidon.csd.auth.gr/papers/PUBLISHED/JOURNAL/pdf/Benetos_TALP.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5299999713897705}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W23980489","https://openalex.org/W32702425","https://openalex.org/W56995320","https://openalex.org/W76301927","https://openalex.org/W200590909","https://openalex.org/W1483217829","https://openalex.org/W1486587503","https://openalex.org/W1562529351","https://openalex.org/W1604938182","https://openalex.org/W1607425652","https://openalex.org/W1661328078","https://openalex.org/W1914599625","https://openalex.org/W1981745143","https://openalex.org/W1984035260","https://openalex.org/W1987621736","https://openalex.org/W1996227995","https://openalex.org/W2024165284","https://openalex.org/W2033468335","https://openalex.org/W2046281481","https://openalex.org/W2052866566","https://openalex.org/W2094810662","https://openalex.org/W2099760476","https://openalex.org/W2101151533","https://openalex.org/W2104298926","https://openalex.org/W2104352833","https://openalex.org/W2113262625","https://openalex.org/W2123497171","https://openalex.org/W2133824856","https://openalex.org/W2136171036","https://openalex.org/W2137171631","https://openalex.org/W2137477262","https://openalex.org/W2138635707","https://openalex.org/W2144920235","https://openalex.org/W2148748626","https://openalex.org/W2159561775","https://openalex.org/W2163318306","https://openalex.org/W2166312020","https://openalex.org/W2167969117","https://openalex.org/W3034415380","https://openalex.org/W3143596294","https://openalex.org/W4229940379","https://openalex.org/W4297787516","https://openalex.org/W6602337844","https://openalex.org/W6624571800","https://openalex.org/W6629060513","https://openalex.org/W6676948963","https://openalex.org/W6682080903"],"related_works":["https://openalex.org/W2601157893","https://openalex.org/W2131735617","https://openalex.org/W2373006798","https://openalex.org/W2049864679","https://openalex.org/W2056912418","https://openalex.org/W2123759770","https://openalex.org/W2033213769","https://openalex.org/W2811390910","https://openalex.org/W4312376745","https://openalex.org/W2082269393"],"abstract_inverted_index":{"<para":[0],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[1],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[2],"Music":[3],"genre":[4,83,166,193],"classification":[5,84,194],"techniques":[6],"are":[7,16,162],"typically":[8],"applied":[9],"to":[10,69],"the":[11,17,41,65,100,107,117,158,177,181,201,205,208],"data":[12,214],"matrix":[13,102],"whose":[14],"columns":[15],"feature":[18,28,55,60,66],"vectors":[19],"extracted":[20,31,153],"from":[21,116,154],"music":[22,48,82],"recordings.":[23],"In":[24],"this":[25],"paper,":[26],"a":[27,33,51,59,73,77,88,123,132,187],"vector":[29,183],"is":[30,75,96,128,152,172,198],"using":[32,85],"texture":[34],"window":[35],"of":[36,43,54,106,119,144,157,176,196,207],"one":[37],"sec,":[38],"which":[39,79,130,161],"enables":[40],"representation":[42],"any":[44,70],"30":[45],"sec":[46],"long":[47],"recording":[49],"as":[50],"time":[52],"sequence":[53],"vectors,":[56],"thus":[57],"yielding":[58],"matrix.":[61],"Consequently,":[62],"by":[63,111,185],"stacking":[64],"matrices":[67],"associated":[68],"dataset":[71],"recordings,":[72],"tensor":[74,93],"created,":[76],"fact":[78],"necessitates":[80],"studying":[81],"tensors.":[86],"First,":[87],"novel":[89,124],"algorithm":[90,109],"for":[91,134,200],"non-negative":[92,101],"factorization":[94],"(NTF)":[95],"derived":[97],"that":[98,175],"extends":[99],"factorization.":[103],"Several":[104],"variants":[105],"NTF":[108,126,169,202],"emerge":[110],"employing":[112],"different":[113],"cost":[114],"functions":[115],"class":[118,136],"Bregman":[120],"divergences.":[121],"Second,":[122],"supervised":[125],"classifier":[127,170,203,211],"proposed,":[129],"trains":[131],"basis":[133,140],"each":[135],"separately":[137],"and":[138,149,180],"employs":[139],"orthogonalization.":[141],"A":[142,192],"variety":[143],"spectral,":[145],"temporal,":[146],"perceptual,":[147],"energy,":[148],"pitch":[150],"descriptors":[151],"1000":[155],"recordings":[156],"GTZAN":[159],"dataset,":[160],"distributed":[163],"across":[164],"10":[165],"classes.":[167],"The":[168],"performance":[171],"compared":[173],"against":[174],"multilayer":[178],"perceptron":[179],"support":[182],"machines":[184],"applying":[186],"stratified":[188],"10-fold":[189],"cross":[190],"validation.":[191],"accuracy":[195],"78.9%":[197],"reported":[199],"demonstrating":[204],"superiority":[206],"aforementioned":[209],"multilinear":[210],"over":[212],"several":[213],"matrix-based":[215],"state-of-the-art":[216],"classifiers.":[217],"</para>":[218]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}