{"id":"https://openalex.org/W4367318870","doi":"https://doi.org/10.1145/3543873.3584626","title":"Bootstrapping Contrastive Learning Enhanced Music Cold-Start Matching","display_name":"Bootstrapping Contrastive Learning Enhanced Music Cold-Start Matching","publication_year":2023,"publication_date":"2023-04-28","ids":{"openalex":"https://openalex.org/W4367318870","doi":"https://doi.org/10.1145/3543873.3584626"},"language":"en","primary_location":{"id":"doi:10.1145/3543873.3584626","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3543873.3584626","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2308.02844","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082323642","display_name":"Xinping Zhao","orcid":"https://orcid.org/0000-0001-6387-1442"},"institutions":[{"id":"https://openalex.org/I4210091137","display_name":"NetEase (China)","ror":"https://ror.org/00fp6fj05","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091137"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinping Zhao","raw_affiliation_strings":["Zhejiang University, China and NetEase Cloud Music, NetEase Inc., China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, China and NetEase Cloud Music, NetEase Inc., China","institution_ids":["https://openalex.org/I4210091137"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015652854","display_name":"Ying Zhang","orcid":"https://orcid.org/0000-0002-0155-8167"},"institutions":[{"id":"https://openalex.org/I4210091137","display_name":"NetEase (China)","ror":"https://ror.org/00fp6fj05","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091137"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Zhang","raw_affiliation_strings":["NetEase Cloud Music, NetEase Inc., China"],"affiliations":[{"raw_affiliation_string":"NetEase Cloud Music, NetEase Inc., China","institution_ids":["https://openalex.org/I4210091137"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064541131","display_name":"Qiang Xiao","orcid":"https://orcid.org/0000-0002-3940-5449"},"institutions":[{"id":"https://openalex.org/I4210091137","display_name":"NetEase (China)","ror":"https://ror.org/00fp6fj05","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091137"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Xiao","raw_affiliation_strings":["NetEase Cloud Music, NetEase Inc., China"],"affiliations":[{"raw_affiliation_string":"NetEase Cloud Music, NetEase Inc., China","institution_ids":["https://openalex.org/I4210091137"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084039256","display_name":"Yuming Ren","orcid":"https://orcid.org/0000-0001-7177-7237"},"institutions":[{"id":"https://openalex.org/I4210091137","display_name":"NetEase (China)","ror":"https://ror.org/00fp6fj05","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091137"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuming Ren","raw_affiliation_strings":["NetEase Cloud Music, NetEase Inc., China"],"affiliations":[{"raw_affiliation_string":"NetEase Cloud Music, NetEase Inc., China","institution_ids":["https://openalex.org/I4210091137"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004770774","display_name":"Yingchun Yang","orcid":"https://orcid.org/0000-0002-3791-9665"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingchun Yang","raw_affiliation_strings":["Zhejiang University, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5082323642"],"corresponding_institution_ids":["https://openalex.org/I4210091137"],"apc_list":null,"apc_paid":null,"fwci":0.8004,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69559024,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"351","last_page":"355"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":1.0,"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":1.0,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9868000149726868,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9843999743461609,"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/computer-science","display_name":"Computer science","score":0.7655562162399292},{"id":"https://openalex.org/keywords/cold-start","display_name":"Cold start (automotive)","score":0.6601550579071045},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5833166837692261},{"id":"https://openalex.org/keywords/bootstrapping","display_name":"Bootstrapping (finance)","score":0.5697504878044128},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.483832985162735},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.46376654505729675},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4472638964653015},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4394083321094513},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.41303202509880066},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.40110671520233154},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3781372308731079},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3250155448913574}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7655562162399292},{"id":"https://openalex.org/C2778956030","wikidata":"https://www.wikidata.org/wiki/Q5142477","display_name":"Cold start (automotive)","level":2,"score":0.6601550579071045},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5833166837692261},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.5697504878044128},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.483832985162735},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.46376654505729675},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4472638964653015},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4394083321094513},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.41303202509880066},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.40110671520233154},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3781372308731079},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3250155448913574},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3543873.3584626","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3543873.3584626","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2308.02844","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2308.02844","pdf_url":"https://arxiv.org/pdf/2308.02844","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:2308.02844","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2308.02844","pdf_url":"https://arxiv.org/pdf/2308.02844","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/16","score":0.7599999904632568,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4367318870.pdf","grobid_xml":"https://content.openalex.org/works/W4367318870.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W10548402","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W2054141820","https://openalex.org/W2140310134","https://openalex.org/W2152790380","https://openalex.org/W2475334473","https://openalex.org/W2512971201","https://openalex.org/W2559655401","https://openalex.org/W2723293840","https://openalex.org/W2733963828","https://openalex.org/W2753686090","https://openalex.org/W2883725317","https://openalex.org/W2896457183","https://openalex.org/W2911319979","https://openalex.org/W2913754224","https://openalex.org/W2941014662","https://openalex.org/W2950180292","https://openalex.org/W2955624969","https://openalex.org/W2962708773","https://openalex.org/W2974819518","https://openalex.org/W2978524555","https://openalex.org/W2998702515","https://openalex.org/W3005680577","https://openalex.org/W3094605801","https://openalex.org/W3098942062","https://openalex.org/W3153325943","https://openalex.org/W3163379884","https://openalex.org/W3164613947","https://openalex.org/W3175362188","https://openalex.org/W3175613352","https://openalex.org/W3199787416","https://openalex.org/W3208338073","https://openalex.org/W4212931205","https://openalex.org/W4221166060","https://openalex.org/W4225385501","https://openalex.org/W4226183797","https://openalex.org/W4285296644","https://openalex.org/W4287253157","https://openalex.org/W4313156423"],"related_works":["https://openalex.org/W1534274833","https://openalex.org/W3117246195","https://openalex.org/W156620619","https://openalex.org/W2616249226","https://openalex.org/W2098233217","https://openalex.org/W2381926679","https://openalex.org/W2914363205","https://openalex.org/W2997844990","https://openalex.org/W1598221548","https://openalex.org/W2081850291"],"abstract_inverted_index":{"We":[0],"study":[1],"a":[2,14,70,107,151],"particular":[3],"matching":[4],"task":[5],"we":[6,18,58,76,89,105,139,191],"call":[7],"Music":[8,64],"Cold-Start":[9,65],"Matching.":[10],"In":[11],"short,":[12],"given":[13],"cold-start":[15,31],"song":[16,32,81,85],"request,":[17],"expect":[19],"to":[20,33,40,78,117,132,149],"retrieve":[21],"songs":[22,39],"with":[23],"similar":[24],"audiences":[25,35,136,160],"and":[26,68,155,169,179,185],"then":[27,156],"fastly":[28],"push":[29],"the":[30,34,37,61,73,119,129,134,158,163,166,170,176,183],"of":[36,63,121,187,201],"retrieved":[38],"warm":[41],"up":[42],"it.":[43],"However,":[44],"there":[45],"are":[46],"hardly":[47],"any":[48],"studies":[49],"done":[50],"on":[51,84,175,195],"this":[52,56,103],"task.":[53],"Therefore,":[54],"in":[55],"paper,":[57],"will":[59],"formalize":[60],"problem":[62],"Matching":[66],"detailedly":[67],"give":[69],"scheme.":[71],"During":[72,128],"offline":[74,177],"training,":[75],"attempt":[77],"learn":[79],"high-quality":[80],"representations":[82,123,148,168],"based":[83],"content":[86],"features.":[87],"But,":[88],"find":[90],"supervision":[91],"signals":[92],"typically":[93],"follow":[94],"power-law":[95],"distribution":[96],"causing":[97],"skewed":[98],"representation":[99],"learning.":[100],"To":[101],"address":[102],"issue,":[104],"propose":[106,140],"novel":[108],"contrastive":[109,126],"learning":[110],"paradigm":[111],"named":[112],"Bootstrapping":[113],"Contrastive":[114],"Learning":[115],"(BCL)":[116],"enhance":[118],"quality":[120],"learned":[122],"by":[124,161],"exerting":[125],"regularization.":[127],"online":[130,180],"serving,":[131],"locate":[133,157],"target":[135,159],"more":[137],"accurately,":[138],"Clustering-based":[141],"Audience":[142],"Targeting":[143],"(CAT)":[144],"that":[145],"clusters":[146],"audience":[147,167],"acquire":[150],"few":[152],"cluster":[153,171],"centroids":[154],"measuring":[162],"relevance":[164],"between":[165],"centroids.":[172],"Extensive":[173],"experiments":[174],"dataset":[178],"system":[181],"demonstrate":[182],"effectiveness":[184],"efficiency":[186],"our":[188],"method.":[189],"Currently,":[190],"have":[192],"deployed":[193],"it":[194],"NetEase":[196],"Cloud":[197],"Music,":[198],"affecting":[199],"millions":[200],"users.":[202]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}