{"id":"https://openalex.org/W3199647641","doi":"https://doi.org/10.1145/3460231.3474228","title":"Shared Neural Item Representations for Completely Cold Start Problem","display_name":"Shared Neural Item Representations for Completely Cold Start Problem","publication_year":2021,"publication_date":"2021-09-13","ids":{"openalex":"https://openalex.org/W3199647641","doi":"https://doi.org/10.1145/3460231.3474228","mag":"3199647641"},"language":"en","primary_location":{"id":"doi:10.1145/3460231.3474228","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460231.3474228","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth ACM Conference on Recommender Systems","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/A5070379115","display_name":"Ramin Raziperchikolaei","orcid":"https://orcid.org/0009-0007-5811-1079"},"institutions":[{"id":"https://openalex.org/I4210144225","display_name":"Rakuten (United States)","ror":"https://ror.org/04bsz5816","country_code":"US","type":"company","lineage":["https://openalex.org/I1301041018","https://openalex.org/I4210144225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ramin Raziperchikolaei","raw_affiliation_strings":["Rakuten, Inc., United States"],"affiliations":[{"raw_affiliation_string":"Rakuten, Inc., United States","institution_ids":["https://openalex.org/I4210144225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018059378","display_name":"Guannan Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144225","display_name":"Rakuten (United States)","ror":"https://ror.org/04bsz5816","country_code":"US","type":"company","lineage":["https://openalex.org/I1301041018","https://openalex.org/I4210144225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guannan Liang","raw_affiliation_strings":["Rakuten, Inc., United States"],"affiliations":[{"raw_affiliation_string":"Rakuten, Inc., United States","institution_ids":["https://openalex.org/I4210144225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109809579","display_name":"Youngjoo Chung","orcid":"https://orcid.org/0000-0002-8997-7947"},"institutions":[{"id":"https://openalex.org/I4210144225","display_name":"Rakuten (United States)","ror":"https://ror.org/04bsz5816","country_code":"US","type":"company","lineage":["https://openalex.org/I1301041018","https://openalex.org/I4210144225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Young-joo Chung","raw_affiliation_strings":["Rakuten, Inc., United States"],"affiliations":[{"raw_affiliation_string":"Rakuten, Inc., United States","institution_ids":["https://openalex.org/I4210144225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070379115"],"corresponding_institution_ids":["https://openalex.org/I4210144225"],"apc_list":null,"apc_paid":null,"fwci":2.7542,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.91763193,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"422","last_page":"431"},"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":0.9944999814033508,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9944000244140625,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7695404291152954},{"id":"https://openalex.org/keywords/cold-start","display_name":"Cold start (automotive)","score":0.6791795492172241},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6536353230476379},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.5808053612709045},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5465564131736755},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5386144518852234},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.47957462072372437},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4466875195503235},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3703334927558899}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7695404291152954},{"id":"https://openalex.org/C2778956030","wikidata":"https://www.wikidata.org/wiki/Q5142477","display_name":"Cold start (automotive)","level":2,"score":0.6791795492172241},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6536353230476379},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.5808053612709045},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5465564131736755},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5386144518852234},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.47957462072372437},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4466875195503235},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3703334927558899},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3460231.3474228","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460231.3474228","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1690919088","https://openalex.org/W1880262756","https://openalex.org/W1994389483","https://openalex.org/W2038585576","https://openalex.org/W2049455633","https://openalex.org/W2054141820","https://openalex.org/W2061460268","https://openalex.org/W2135790056","https://openalex.org/W2137028279","https://openalex.org/W2145094598","https://openalex.org/W2155119555","https://openalex.org/W2157881433","https://openalex.org/W2172249709","https://openalex.org/W2218318129","https://openalex.org/W2403286959","https://openalex.org/W2471920251","https://openalex.org/W2605246672","https://openalex.org/W2605350416","https://openalex.org/W2608239929","https://openalex.org/W2616376319","https://openalex.org/W2740920897","https://openalex.org/W2741249238","https://openalex.org/W2753686090","https://openalex.org/W2767724106","https://openalex.org/W2802187397","https://openalex.org/W2897212375","https://openalex.org/W2903296288","https://openalex.org/W2904012554","https://openalex.org/W2949821452","https://openalex.org/W2950495035","https://openalex.org/W2962712142","https://openalex.org/W2963902947","https://openalex.org/W2964983698","https://openalex.org/W2978524555","https://openalex.org/W3093028121","https://openalex.org/W3102560000","https://openalex.org/W3102895136","https://openalex.org/W3154513746","https://openalex.org/W4299828299"],"related_works":["https://openalex.org/W2529147798","https://openalex.org/W1979350723","https://openalex.org/W2555127516","https://openalex.org/W2528269032","https://openalex.org/W2964047085","https://openalex.org/W3180903918","https://openalex.org/W4313327643","https://openalex.org/W3207757380","https://openalex.org/W2358294942","https://openalex.org/W4367460280"],"abstract_inverted_index":{"Neural":[0],"networks":[1,26],"have":[2],"become":[3],"popular":[4],"recently":[5],"in":[6,32,94,158,187,197],"recommendation":[7],"systems":[8],"to":[9,135,194,204],"extract":[10],"user":[11,23,28,55,114,121],"and":[12,24,29,35,63,106,116,129,140,161,175,190],"item":[13,25,30,41,65,69,93,104,148],"representations.":[14,122,170],"Most":[15],"previous":[16,206],"works":[17],"follow":[18],"a":[19],"two-branch":[20],"setting,":[21],"where":[22,44],"learn":[27],"representations":[31,88,125,139],"the":[33,40,45,49,54,61,64,68,74,95,100,103,107,113,137,143,147,166,169,195,198,205],"first":[34],"second":[36],"branches,":[37],"respectively.":[38],"In":[39,76],"cold-start":[42],"problem,":[43],"usage":[46],"patterns":[47],"of":[48,102,168,200],"items":[50],"do":[51],"not":[52],"exist,":[53],"network":[56,66,105,115],"uses":[57,67],"ID/interaction":[58],"vector":[59],"as":[60,73],"input":[62],"side":[70],"information":[71],"(content)":[72],"input.":[75],"this":[77,85],"paper,":[78],"we":[79,151],"will":[80,152],"show":[81,153,178],"that":[82,179],"by":[83,146],"using":[84],"structure,":[86],"two":[87,124,138],"are":[89],"learned":[90],"for":[91,119],"each":[92],"training":[96,127,201],"set;":[97],"one":[98,109,144],"is":[99,110,117,191],"output":[101],"other":[108],"hidden":[111],"inside":[112],"used":[118],"learning":[120],"Learning":[123],"makes":[126],"slower":[128],"optimization":[130],"more":[131,192],"difficult.":[132],"We":[133],"propose":[134],"unify":[136],"only":[141],"use":[142],"generated":[145],"network.":[149],"Also,":[150],"how":[154,162],"attention":[155],"mechanisms":[156],"fit":[157],"our":[159,180],"setting":[160],"they":[163],"can":[164],"improve":[165],"quality":[167],"Our":[171],"results":[172],"on":[173],"public":[174],"real-world":[176],"datasets":[177],"approach":[181],"converges":[182],"faster,":[183],"achieves":[184],"higher":[185],"recall":[186],"fewer":[188],"iterations,":[189],"robust":[193],"changes":[196],"number":[199],"samples":[202],"compared":[203],"works.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
