{"id":"https://openalex.org/W4407654895","doi":"https://doi.org/10.1145/3718488","title":"Balancing Embedding Spectrum for Recommendation","display_name":"Balancing Embedding Spectrum for Recommendation","publication_year":2025,"publication_date":"2025-02-17","ids":{"openalex":"https://openalex.org/W4407654895","doi":"https://doi.org/10.1145/3718488"},"language":"en","primary_location":{"id":"doi:10.1145/3718488","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3718488","pdf_url":null,"source":{"id":"https://openalex.org/S4387284325","display_name":"ACM Transactions on Recommender Systems","issn_l":"2770-6699","issn":["2770-6699"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Recommender Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3718488","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103242807","display_name":"Shaowen Peng","orcid":"https://orcid.org/0000-0003-4020-9100"},"institutions":[{"id":"https://openalex.org/I75917431","display_name":"Nara Institute of Science and Technology","ror":"https://ror.org/05bhada84","country_code":"JP","type":"education","lineage":["https://openalex.org/I75917431"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shaowen Peng","raw_affiliation_strings":["Nara Institute of Science and Technology, Ikoma, Japan","Nara Institute of Science and Technology,  Ikoma, Japan"],"raw_orcid":"https://orcid.org/0000-0003-4020-9100","affiliations":[{"raw_affiliation_string":"Nara Institute of Science and Technology, Ikoma, Japan","institution_ids":["https://openalex.org/I75917431"]},{"raw_affiliation_string":"Nara Institute of Science and Technology,  Ikoma, Japan","institution_ids":["https://openalex.org/I75917431"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075581979","display_name":"Kazunari Sugiyama","orcid":"https://orcid.org/0000-0003-3962-821X"},"institutions":[{"id":"https://openalex.org/I4210105506","display_name":"Osaka Seikei University","ror":"https://ror.org/00yydx071","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210105506"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazunari Sugiyama","raw_affiliation_strings":["Osaka Seikei University, Osaka, Japan","Osaka Seikei University,  Osaka Japan"],"raw_orcid":"https://orcid.org/0000-0003-3962-821X","affiliations":[{"raw_affiliation_string":"Osaka Seikei University, Osaka, Japan","institution_ids":["https://openalex.org/I4210105506"]},{"raw_affiliation_string":"Osaka Seikei University,  Osaka Japan","institution_ids":["https://openalex.org/I4210105506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011513741","display_name":"Xin Liu","orcid":"https://orcid.org/0000-0002-2336-7409"},"institutions":[{"id":"https://openalex.org/I4210164862","display_name":"Artificial Intelligence in Medicine (Canada)","ror":"https://ror.org/05p590m36","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210164862"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xin Liu","raw_affiliation_strings":["Artificial Intelligence Research Center, Koto-ku, Japan","Artificial Intelligence Research Center,  Koto-ku, Japan"],"raw_orcid":"https://orcid.org/0000-0002-2336-7409","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Center, Koto-ku, Japan","institution_ids":["https://openalex.org/I4210164862"]},{"raw_affiliation_string":"Artificial Intelligence Research Center,  Koto-ku, Japan","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001584274","display_name":"Tsunenori Mine","orcid":"https://orcid.org/0000-0002-7462-8074"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tsunenori Mine","raw_affiliation_strings":["Kyushu University, Fukuoka, Japan","Kyushu University,  Fukuoka, Japan"],"raw_orcid":"https://orcid.org/0000-0002-7462-8074","affiliations":[{"raw_affiliation_string":"Kyushu University, Fukuoka, Japan","institution_ids":["https://openalex.org/I135598925"]},{"raw_affiliation_string":"Kyushu University,  Fukuoka, Japan","institution_ids":["https://openalex.org/I135598925"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03108085,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":"4","first_page":"1","last_page":"25"},"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/T10028","display_name":"Topic Modeling","score":0.9944999814033508,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9858999848365784,"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":0.5561846494674683},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5292912125587463},{"id":"https://openalex.org/keywords/spectrum","display_name":"Spectrum (functional analysis)","score":0.46973952651023865},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15887287259101868},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10796597599983215}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5561846494674683},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5292912125587463},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.46973952651023865},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15887287259101868},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10796597599983215},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3718488","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3718488","pdf_url":null,"source":{"id":"https://openalex.org/S4387284325","display_name":"ACM Transactions on Recommender Systems","issn_l":"2770-6699","issn":["2770-6699"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Recommender Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3718488","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3718488","pdf_url":null,"source":{"id":"https://openalex.org/S4387284325","display_name":"ACM Transactions on Recommender Systems","issn_l":"2770-6699","issn":["2770-6699"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Recommender Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W39762900","https://openalex.org/W398859631","https://openalex.org/W1698699930","https://openalex.org/W1720514416","https://openalex.org/W1987431925","https://openalex.org/W1993897382","https://openalex.org/W2017921654","https://openalex.org/W2042281163","https://openalex.org/W2054141820","https://openalex.org/W2069870183","https://openalex.org/W2340502990","https://openalex.org/W2560674852","https://openalex.org/W2591957553","https://openalex.org/W2605350416","https://openalex.org/W2741249238","https://openalex.org/W2787933113","https://openalex.org/W2807021761","https://openalex.org/W2897636232","https://openalex.org/W2913023375","https://openalex.org/W2945827670","https://openalex.org/W2963367478","https://openalex.org/W2963601856","https://openalex.org/W2964051675","https://openalex.org/W2984100107","https://openalex.org/W2999649805","https://openalex.org/W3035060554","https://openalex.org/W3041537557","https://openalex.org/W3045200674","https://openalex.org/W3094605801","https://openalex.org/W3100278010","https://openalex.org/W3100848837","https://openalex.org/W3142239405","https://openalex.org/W3153325943","https://openalex.org/W3170097025","https://openalex.org/W3171007011","https://openalex.org/W3209428314","https://openalex.org/W4214689175","https://openalex.org/W4283702870","https://openalex.org/W4284680110","https://openalex.org/W4306317072","https://openalex.org/W4384644330","https://openalex.org/W4390489709","https://openalex.org/W4400524976","https://openalex.org/W4401863225"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2081900870","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890"],"abstract_inverted_index":{"Modern":[0],"recommender":[1,230],"systems":[2],"heavily":[3],"rely":[4],"on":[5,43,227],"high-quality":[6],"representations":[7,32,57],"learned":[8],"from":[9],"high-dimensional":[10],"sparse":[11],"data.":[12],"While":[13,102],"significant":[14],"efforts":[15],"have":[16,33],"been":[17],"invested":[18],"in":[19,46,192],"designing":[20],"powerful":[21],"algorithms":[22,160],"for":[23],"extracting":[24],"user":[25],"preferences,":[26],"the":[27,47,56,64,75,118,139,150,178,189,216],"factors":[28],"contributing":[29],"to":[30,59,69,88,96,98,116,121,142,185,214],"good":[31],"remained":[34],"relatively":[35],"unexplored.":[36],"In":[37],"this":[38,108,127],"work,":[39],"we":[40,79,129,174,205],"shed":[41],"light":[42],"an":[44,122,207],"issue":[45,109],"existing":[48],"pairwise":[49],"learning":[50,133,159],"paradigm":[51,134],"(i.e.,":[52],"embedding":[53,66,152,217],"collapse),":[54],"that":[55,81,144,156,176],"tend":[58],"span":[60,149],"a":[61,70,89,99,113,131,193],"subspace":[62],"of":[63,83,171,198],"whole":[65],"space,":[67],"leading":[68,120],"suboptimal":[71],"solution":[72],"and":[73,94,146,201,209,221,234,242],"reducing":[74],"model":[76],"capacity.":[77],"Specifically,":[78],"show":[80,175],"alignment":[82,197],"positive":[84,199],"pairs":[85,200],"is":[86],"equivalent":[87],"low-pass":[90],"filter":[91,115],"causing":[92],"users":[93,145],"items":[95,147],"collapse":[97],"constant":[100],"vector.":[101],"negative":[103,163],"sampling":[104,164],"can":[105,165],"partially":[106],"mitigate":[107],"by":[110],"acting":[111],"as":[112,168],"high-pass":[114],"balance":[117,195,215],"spectrum,":[119],"incomplete":[123],"collapse.":[124],"To":[125],"tackle":[126],"issue,":[128],"present":[130],"novel":[132],"DirectSpec,":[135],"which":[136],"directly":[137],"optimizes":[138],"spectrum":[140,179,202,218],"distribution":[141],"ensure":[143],"effectively":[148],"entire":[151],"space.":[153],"We":[154,223],"demonstrate":[155,239],"many":[157],"self-supervised":[158],"without":[161],"explicit":[162],"be":[166,183],"considered":[167],"special":[169],"cases":[170],"DirectSpec.":[172],"Furthermore,":[173],"optimizing":[177],"inappropriately":[180],"could":[181],"also":[182],"detrimental":[184],"data":[186],"representation,":[187],"where":[188],"key":[190],"lies":[191],"dynamic":[194],"between":[196],"balancing.":[203],"Finally,":[204],"propose":[206],"enhanced":[208],"practical":[210],"implementation":[211],"DirectSpec":[212,225],"+":[213,226],"more":[219],"adaptively":[220],"effectively.":[222],"implement":[224],"two":[228],"popular":[229],"models:":[231],"matrix":[232],"factorization":[233],"LightGCN.":[235],"Our":[236],"experimental":[237],"results":[238],"its":[240],"effectiveness":[241],"efficiency":[243],"over":[244],"competitive":[245],"baselines.":[246]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}