{"id":"https://openalex.org/W4288804669","doi":"https://doi.org/10.1145/3523227.3546768","title":"Exploiting Negative Preference in Content-based Music Recommendation with Contrastive Learning","display_name":"Exploiting Negative Preference in Content-based Music Recommendation with Contrastive Learning","publication_year":2022,"publication_date":"2022-09-13","ids":{"openalex":"https://openalex.org/W4288804669","doi":"https://doi.org/10.1145/3523227.3546768"},"language":"en","primary_location":{"id":"doi:10.1145/3523227.3546768","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523227.3546768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2207.13909","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101408067","display_name":"Minju Park","orcid":"https://orcid.org/0000-0002-2588-2674"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Minju Park","raw_affiliation_strings":["Department of Intelligence and Information, Seoul National University, Korea, Republic of"],"affiliations":[{"raw_affiliation_string":"Department of Intelligence and Information, Seoul National University, Korea, Republic of","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088852010","display_name":"Kyogu Lee","orcid":"https://orcid.org/0000-0002-4210-0312"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyogu Lee","raw_affiliation_strings":["Department of Intelligence and Information, Graduate School of AI, AI Institute, Seoul National University, Korea, Republic of"],"affiliations":[{"raw_affiliation_string":"Department of Intelligence and Information, Graduate School of AI, AI Institute, Seoul National University, Korea, Republic of","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101408067"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":2.8295,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.91172793,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"229","last_page":"236"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9998000264167786,"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":0.9998000264167786,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9944000244140625,"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/T10788","display_name":"Neuroscience and Music Perception","score":0.9919000267982483,"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/preference","display_name":"Preference","score":0.8161324262619019},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.71976637840271},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5811728835105896},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4483802914619446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42175695300102234},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38347986340522766},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.372795045375824},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.3309110999107361},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.33033132553100586},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16465270519256592},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.14633473753929138},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1283787488937378}],"concepts":[{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.8161324262619019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.71976637840271},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5811728835105896},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4483802914619446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42175695300102234},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38347986340522766},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.372795045375824},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.3309110999107361},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33033132553100586},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16465270519256592},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.14633473753929138},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1283787488937378},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3523227.3546768","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523227.3546768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2207.13909","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.13909","pdf_url":"https://arxiv.org/pdf/2207.13909","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2207.13909","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.13909","pdf_url":"https://arxiv.org/pdf/2207.13909","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5400000214576721,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1593136224","display_name":null,"funder_award_id":"R2022020066","funder_id":"https://openalex.org/F4320322006","funder_display_name":"Ministry of Culture, Sports and Tourism"},{"id":"https://openalex.org/G4709003234","display_name":null,"funder_award_id":"2022-0-00320","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320322006","display_name":"Ministry of Culture, Sports and Tourism","ror":"https://ror.org/02fkk6k65"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1497613135","https://openalex.org/W1566742530","https://openalex.org/W1880298565","https://openalex.org/W1964786562","https://openalex.org/W1971040550","https://openalex.org/W2048039201","https://openalex.org/W2066432005","https://openalex.org/W2069994409","https://openalex.org/W2097638479","https://openalex.org/W2101409192","https://openalex.org/W2108630796","https://openalex.org/W2115568835","https://openalex.org/W2124074612","https://openalex.org/W2127870748","https://openalex.org/W2134990037","https://openalex.org/W2137028279","https://openalex.org/W2514091133","https://openalex.org/W2749914647","https://openalex.org/W2752796333","https://openalex.org/W2798435682","https://openalex.org/W2799023274","https://openalex.org/W2892391771","https://openalex.org/W2914665399","https://openalex.org/W2920845749","https://openalex.org/W2950060770","https://openalex.org/W2952925178","https://openalex.org/W2963451564","https://openalex.org/W2963799213","https://openalex.org/W2967638906","https://openalex.org/W2971074500","https://openalex.org/W2972737975","https://openalex.org/W3005680577","https://openalex.org/W3034718811","https://openalex.org/W3091905774","https://openalex.org/W3101366597","https://openalex.org/W3132970391","https://openalex.org/W3159717324","https://openalex.org/W3185820380","https://openalex.org/W4226175735","https://openalex.org/W4226181975","https://openalex.org/W4226280022","https://openalex.org/W4287802874"],"related_works":["https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W2056712470","https://openalex.org/W3125580266","https://openalex.org/W4288390103","https://openalex.org/W4317039510","https://openalex.org/W1657011257"],"abstract_inverted_index":{"Advanced":[0],"music":[1,21,32,45,80,84,147],"recommendation":[2,22,46,85],"systems":[3,47],"are":[4],"being":[5],"introduced":[6],"along":[7],"with":[8,87,94,127],"the":[9,36,73,117,120,140,156,166,184,187],"development":[10],"of":[11,38,59,75,102,119,131,142,175,178,186],"machine":[12],"learning.":[13],"However,":[14],"it":[15],"is":[16],"essential":[17],"to":[18,44,65],"design":[19],"a":[20,57,128,171],"system":[23,126],"that":[24,153],"can":[25],"increase":[26],"user":[27],"satisfaction":[28],"by":[29,35,82,123],"understanding":[30],"users\u2019":[31,79],"tastes,":[33],"not":[34],"complexity":[37],"models.":[39],"Although":[40],"several":[41],"studies":[42],"related":[43],"exploiting":[48,90,100,143],"negative":[49,76,106,112,121,144],"preferences":[50,101],"have":[51],"shown":[52],"performance":[53],"improvements,":[54],"there":[55],"was":[56],"lack":[58],"explanation":[60],"on":[61],"how":[62],"they":[63],"led":[64],"better":[66],"recommendations.":[67,148],"In":[68],"this":[69],"work,":[70],"we":[71],"analyze":[72],"role":[74],"preference":[77,91,122,145],"in":[78,146,159],"tastes":[81],"comparing":[83],"models":[86],"contrastive":[88],"learning":[89],"(CLEP)":[92],"but":[93],"three":[95],"different":[96,176],"training":[97,168],"strategies":[98,169],"-":[99],"both":[103],"positive":[104,108,163],"and":[105,111,137,161],"(CLEP-PN),":[107],"only":[109,113],"(CLEP-P),":[110],"(CLEP-N).":[114],"We":[115],"evaluate":[116],"effectiveness":[118],"validating":[124],"each":[125],"small":[129],"amount":[130],"personalized":[132],"data":[133],"obtained":[134],"via":[135],"survey":[136],"further":[138],"illuminate":[139],"possibility":[141],"Our":[149],"experimental":[150],"results":[151],"show":[152],"CLEP-N":[154],"outperforms":[155],"other":[157],"two":[158],"accuracy":[160],"false":[162],"rate.":[164],"Furthermore,":[165],"proposed":[167,188],"produced":[170],"consistent":[172],"tendency":[173],"regardless":[174],"types":[177],"front-end":[179],"musical":[180],"feature":[181],"extractors,":[182],"proving":[183],"stability":[185],"method.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2022-07-30T00:00:00"}