{"id":"https://openalex.org/W4293518949","doi":"https://doi.org/10.1109/icme52920.2022.9859863","title":"They Like Comedy, Don't You? A Cluster-Based Meta-Learning for Cold-Start Recommendation","display_name":"They Like Comedy, Don't You? A Cluster-Based Meta-Learning for Cold-Start Recommendation","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4293518949","doi":"https://doi.org/10.1109/icme52920.2022.9859863"},"language":"en","primary_location":{"id":"doi:10.1109/icme52920.2022.9859863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme52920.2022.9859863","pdf_url":null,"source":{"id":"https://openalex.org/S4363607799","display_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-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/A5100767957","display_name":"Feng Jiang","orcid":"https://orcid.org/0009-0001-6271-9526"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feng Jiang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013151664","display_name":"Qianfang Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianfang Xu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100359871","display_name":"Wenliang Li","orcid":"https://orcid.org/0000-0002-0864-0358"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenliang Li","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103250251","display_name":"Bo Xiao","orcid":"https://orcid.org/0000-0003-2206-1712"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Xiao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101911385","display_name":"Yuhao Luo","orcid":"https://orcid.org/0000-0002-9004-0756"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhao Luo","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100767957"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.1457,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.39399652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9495000243186951,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.8853506445884705},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8142338991165161},{"id":"https://openalex.org/keywords/cold-start","display_name":"Cold start (automotive)","score":0.7758490443229675},{"id":"https://openalex.org/keywords/movielens","display_name":"MovieLens","score":0.6123406887054443},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.5618239045143127},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.5108620524406433},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.42056381702423096},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34620189666748047},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2907114028930664},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.08152532577514648},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07189309597015381}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.8853506445884705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8142338991165161},{"id":"https://openalex.org/C2778956030","wikidata":"https://www.wikidata.org/wiki/Q5142477","display_name":"Cold start (automotive)","level":2,"score":0.7758490443229675},{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.6123406887054443},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.5618239045143127},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.5108620524406433},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.42056381702423096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34620189666748047},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2907114028930664},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.08152532577514648},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07189309597015381},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme52920.2022.9859863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme52920.2022.9859863","pdf_url":null,"source":{"id":"https://openalex.org/S4363607799","display_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8719100474","display_name":null,"funder_award_id":"62076031","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2002834872","https://openalex.org/W2604662567","https://openalex.org/W2604763608","https://openalex.org/W2605350416","https://openalex.org/W2624407581","https://openalex.org/W2753686090","https://openalex.org/W2796608345","https://openalex.org/W2945827670","https://openalex.org/W2946757877","https://openalex.org/W2955624969","https://openalex.org/W2963522561","https://openalex.org/W2963878746","https://openalex.org/W2964983698","https://openalex.org/W3012847895","https://openalex.org/W3043239945","https://openalex.org/W3081320135","https://openalex.org/W3098400049","https://openalex.org/W3100278010","https://openalex.org/W3112334685","https://openalex.org/W3177379791","https://openalex.org/W4300514939","https://openalex.org/W6681968150","https://openalex.org/W6736057607","https://openalex.org/W6744107841","https://openalex.org/W6751959828","https://openalex.org/W6763049584","https://openalex.org/W6787590773","https://openalex.org/W6787818716"],"related_works":["https://openalex.org/W2355698112","https://openalex.org/W2022984797","https://openalex.org/W4394818607","https://openalex.org/W2986679525","https://openalex.org/W2797500822","https://openalex.org/W2735929803","https://openalex.org/W2954356050","https://openalex.org/W2113380565","https://openalex.org/W3002169615","https://openalex.org/W2081388176"],"abstract_inverted_index":{"Cold":[0],"start":[1,73],"has":[2],"always":[3],"been":[4],"a":[5,66,83],"challenging":[6],"problem":[7],"due":[8],"to":[9,53,86],"the":[10,32,71,77,88,97,108,120,123,138,141],"sparse":[11],"user-item":[12],"interaction.":[13],"Recently":[14],"meta-learning":[15,124],"models":[16],"have":[17],"performed":[18],"outstandingly":[19],"in":[20,70,116,143],"solving":[21],"this":[22,49,103],"problem,":[23],"which":[24],"train":[25],"an":[26],"optimal":[27,99],"initialization":[28,90,100],"parameter":[29],"by":[30,93],"sharing":[31,39],"knowledge":[33,38,55],"of":[34,122,140],"all":[35],"users.":[36],"However,":[37],"between":[40],"users":[41,58,112],"with":[42,59,76,113],"different":[43],"preferences":[44],"is":[45],"negatively":[46],"affected.":[47],"In":[48,102],"paper,":[50],"we":[51,63,81,105],"try":[52],"share":[54],"only":[56],"among":[57,111],"similar":[60],"interests.":[61],"Specifically,":[62],"first":[64],"propose":[65],"user":[67],"cluster":[68,79,98],"method":[69,135],"cold":[72],"scenario.":[74],"Then,":[75],"user's":[78],"information":[80],"design":[82],"conversion":[84],"network":[85],"transform":[87],"global":[89],"parameters":[91],"learned":[92],"meta":[94],"learning":[95],"into":[96],"parameters.":[101],"way,":[104],"can":[106],"reduce":[107],"negative":[109],"impact":[110],"large":[114],"differences":[115],"preferences,":[117],"and":[118,130,147],"improve":[119],"performance":[121],"model.":[125],"Extensive":[126],"experiments":[127],"on":[128],"MovieLens":[129],"Yelp":[131],"demonstrate":[132],"that":[133],"our":[134],"significantly":[136],"outperforms":[137],"state":[139],"arts":[142],"both":[144],"warm":[145],"up":[146],"cold-start":[148],"scenarios.":[149]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
