{"id":"https://openalex.org/W4396758758","doi":"https://doi.org/10.1145/3589334.3645577","title":"Enhancing Recommendation Accuracy and Diversity with Box Embedding: A Universal Framework","display_name":"Enhancing Recommendation Accuracy and Diversity with Box Embedding: A Universal Framework","publication_year":2024,"publication_date":"2024-05-08","ids":{"openalex":"https://openalex.org/W4396758758","doi":"https://doi.org/10.1145/3589334.3645577"},"language":"en","primary_location":{"id":"doi:10.1145/3589334.3645577","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589334.3645577","pdf_url":null,"source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3589334.3645577","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018073139","display_name":"Cheng Wu","orcid":"https://orcid.org/0009-0002-4481-405X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Wu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-4481-405X","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038518790","display_name":"Shaoyun Shi","orcid":"https://orcid.org/0000-0002-1524-7132"},"institutions":[{"id":"https://openalex.org/I4210127820","display_name":"Zhejiang Hisun Pharmaceutical (China)","ror":"https://ror.org/03j93xk55","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210127820"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoyun Shi","raw_affiliation_strings":["Kuaishou Inc., Hangzhou, Zhejiang, China"],"raw_orcid":"https://orcid.org/0000-0002-1524-7132","affiliations":[{"raw_affiliation_string":"Kuaishou Inc., Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I4210127820"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047153705","display_name":"Chaokun Wang","orcid":"https://orcid.org/0000-0002-2986-2574"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaokun Wang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2986-2574","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028943556","display_name":"Ziyang Liu","orcid":"https://orcid.org/0009-0007-4238-1533"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyang Liu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-4238-1533","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039704400","display_name":"Wang Peng","orcid":"https://orcid.org/0009-0008-5100-9546"},"institutions":[{"id":"https://openalex.org/I4210127820","display_name":"Zhejiang Hisun Pharmaceutical (China)","ror":"https://ror.org/03j93xk55","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210127820"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Peng","raw_affiliation_strings":["Kuaishou Inc., Hangzhou, Zhejiang, China"],"raw_orcid":"https://orcid.org/0009-0008-5100-9546","affiliations":[{"raw_affiliation_string":"Kuaishou Inc., Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I4210127820"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033912311","display_name":"Wenjin Wu","orcid":"https://orcid.org/0009-0001-3018-4598"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenjin Wu","raw_affiliation_strings":["Kuaishou Inc., Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-3018-4598","affiliations":[{"raw_affiliation_string":"Kuaishou Inc., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039756970","display_name":"Dongying Kong","orcid":"https://orcid.org/0009-0002-9100-0964"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dongying Kong","raw_affiliation_strings":["Kuaishou Inc., Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-9100-0964","affiliations":[{"raw_affiliation_string":"Kuaishou Inc., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020615530","display_name":"Han Li","orcid":"https://orcid.org/0009-0000-9801-9292"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han Li","raw_affiliation_strings":["Kuaishou Inc., Beijing, China"],"raw_orcid":"https://orcid.org/0009-0000-9801-9292","affiliations":[{"raw_affiliation_string":"Kuaishou Inc., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062939922","display_name":"Kun Gai","orcid":"https://orcid.org/0000-0002-3636-3618"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kun Gai","raw_affiliation_strings":["Unaffiliated, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3636-3618","affiliations":[{"raw_affiliation_string":"Unaffiliated, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3756","last_page":"3766"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"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":1.0,"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":0.9854999780654907,"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":0.9754999876022339,"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":0.8077585697174072},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6120789051055908},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5942001342773438},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.556554913520813},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5329680442810059},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5221602916717529},{"id":"https://openalex.org/keywords/diversity","display_name":"Diversity (politics)","score":0.4983656406402588},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.44021308422088623},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.4366748332977295},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4138426184654236},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.41113418340682983},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34209898114204407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3125607371330261},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.233184814453125},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09156164526939392}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8077585697174072},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6120789051055908},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5942001342773438},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.556554913520813},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5329680442810059},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5221602916717529},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.4983656406402588},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.44021308422088623},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.4366748332977295},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4138426184654236},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.41113418340682983},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34209898114204407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3125607371330261},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.233184814453125},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09156164526939392},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","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},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589334.3645577","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589334.3645577","pdf_url":null,"source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3589334.3645577","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589334.3645577","pdf_url":null,"source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4695069324","display_name":null,"funder_award_id":"No.62372264","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1720514416","https://openalex.org/W1990550419","https://openalex.org/W2054141820","https://openalex.org/W2092044939","https://openalex.org/W2129619434","https://openalex.org/W2140942692","https://openalex.org/W2153578526","https://openalex.org/W2170341854","https://openalex.org/W2219888463","https://openalex.org/W2225560834","https://openalex.org/W2340502990","https://openalex.org/W2508625104","https://openalex.org/W2604639157","https://openalex.org/W2605350416","https://openalex.org/W2783565819","https://openalex.org/W2798307797","https://openalex.org/W2911575572","https://openalex.org/W2945827670","https://openalex.org/W2963331552","https://openalex.org/W2963690776","https://openalex.org/W2965286893","https://openalex.org/W2966283114","https://openalex.org/W2997014384","https://openalex.org/W3034503922","https://openalex.org/W3035606589","https://openalex.org/W3040868708","https://openalex.org/W3045200674","https://openalex.org/W3080884086","https://openalex.org/W3091814605","https://openalex.org/W3100278010","https://openalex.org/W3100591234","https://openalex.org/W3102362806","https://openalex.org/W3117719172","https://openalex.org/W3138773240","https://openalex.org/W3152663991","https://openalex.org/W3162402131","https://openalex.org/W3167617922","https://openalex.org/W3168355451","https://openalex.org/W3169799753","https://openalex.org/W3178835722","https://openalex.org/W4212774754","https://openalex.org/W4224325265","https://openalex.org/W4284701460","https://openalex.org/W4287724053","https://openalex.org/W4289690012","https://openalex.org/W4292423901","https://openalex.org/W4306317369","https://openalex.org/W4378771633","https://openalex.org/W4384648463","https://openalex.org/W4385270482","https://openalex.org/W4385568076","https://openalex.org/W4387451903","https://openalex.org/W6602855854","https://openalex.org/W6689251992","https://openalex.org/W6727233892","https://openalex.org/W6766516199"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W2793211469","https://openalex.org/W2949152769","https://openalex.org/W4390273403","https://openalex.org/W4372354731","https://openalex.org/W2942366970","https://openalex.org/W2807634898","https://openalex.org/W4386781444","https://openalex.org/W1692008701","https://openalex.org/W1968265719"],"abstract_inverted_index":{"Recommender":[0],"systems":[1],"have":[2],"emerged":[3],"as":[4,165,167],"an":[5],"indispensable":[6],"mean":[7],"to":[8,37,52,62,97,109,131,230],"meet":[9],"personalized":[10,154],"interests":[11],"of":[12,66,150,198,204,248],"users":[13,36,111,138],"and":[14,69,112,121,139,148,152,221,227],"alleviate":[15],"information":[16,27],"overload.":[17],"Despite":[18],"the":[19,64,133,146,189,196,202,246],"great":[20],"success,":[21],"accuracy-oriented":[22],"recommendation":[23,54,99,102,185,219,233],"models":[24,56],"are":[25],"creating":[26],"cocoons,":[28],"i.e.,":[29],"it":[30],"is":[31,74,129,228],"becoming":[32],"increasingly":[33],"difficult":[34],"for":[35,76,117,181],"see":[38],"other":[39],"items":[40,113],"they":[41],"might":[42],"be":[43],"interested":[44],"in.":[45],"Although":[46],"recent":[47],"studies":[48],"start":[49],"paying":[50],"attention":[51,163],"enhancing":[53],"diversity,":[55,186],"based":[57,93],"on":[58,94,184,209],"point":[59],"embedding":[60,96,116],"fail":[61],"describe":[63],"range":[65],"user":[67,169],"preferences":[68],"item":[70],"features":[71],"well,":[72],"which":[73,187],"essential":[75],"diversified":[77],"matching.":[78],"To":[79,141],"this":[80],"end,":[81],"we":[82,157,176],"propose":[83],"LCD-UC":[84,106,215,243],",":[85],"a":[86,124,143,160,168,249],"novel":[87],"List-Check-Decide":[88],"framework":[89],"with":[90,101],"UnCertainty":[91],"masking":[92,171],"box":[95,115],"improve":[98,217,245],"diversity":[100,149,155,222],"accuracy":[103,147,220],"maintained.":[104],"Specifically,":[105],"creates":[107],"hypercubes":[108,136],"represent":[110],"using":[114],"high":[118],"model":[119],"flexibility":[120],"expressiveness.":[122],"Then,":[123],"hypercube":[125],"similarity":[126,134],"scoring":[127],"function":[128],"designed":[130],"measure":[132],"between":[135,145],"representing":[137],"items.":[140],"make":[142],"balance":[144],"recommendations":[151],"achieve":[153],"needs,":[156],"further":[158],"develop":[159],"user-item":[161],"pairwise":[162],"mechanism":[164,172],"well":[166],"uncertainty":[170],"in":[173],"LCD-UC.":[174],"Besides,":[175],"present":[177],"two":[178],"new":[179],"metrics":[180,193],"better":[182],"evaluation":[183],"address":[188],"issue":[190],"that":[191,214,242],"existing":[192],"only":[194],"consider":[195],"coverage":[197],"categories":[199],"while":[200],"ignore":[201],"frequency":[203],"categories.":[205],"The":[206],"extensive":[207],"experiments":[208],"three":[210,224],"real-world":[211,250],"datasets":[212],"show":[213],"can":[216,244],"both":[218],"over":[223],"base":[225],"models,":[226],"superior":[229],"six":[231],"state-of-the-art":[232],"models.":[234],"An":[235],"online":[236],"10-day":[237],"AB":[238],"test":[239],"also":[240],"demonstrates":[241],"performance":[247],"advertising":[251],"system.":[252]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}