{"id":"https://openalex.org/W4409657215","doi":"https://doi.org/10.1145/3696410.3714663","title":"Frequency-Augmented Mixture-of-Heterogeneous-Experts Framework for Sequential Recommendation","display_name":"Frequency-Augmented Mixture-of-Heterogeneous-Experts Framework for Sequential Recommendation","publication_year":2025,"publication_date":"2025-04-22","ids":{"openalex":"https://openalex.org/W4409657215","doi":"https://doi.org/10.1145/3696410.3714663"},"language":"en","primary_location":{"id":"doi:10.1145/3696410.3714663","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3696410.3714663","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714663","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714663","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102844742","display_name":"Junjie Zhang","orcid":"https://orcid.org/0009-0008-8864-915X"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junjie Zhang","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101577090","display_name":"Ruobing Xie","orcid":"https://orcid.org/0000-0003-3170-5647"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruobing Xie","raw_affiliation_strings":["Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101796004","display_name":"Hongyu Lu","orcid":"https://orcid.org/0000-0002-0247-2496"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Lu","raw_affiliation_strings":["Tencent, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Tencent, Guangzhou, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044309642","display_name":"Wenqi Sun","orcid":"https://orcid.org/0000-0003-2230-4219"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqi Sun","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037145565","display_name":"Wayne Xin Zhao","orcid":"https://orcid.org/0000-0002-8333-6196"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wayne Xin Zhao","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108579011","display_name":"Yu Chen","orcid":"https://orcid.org/0000-0002-5572-7173"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Chen","raw_affiliation_strings":["Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020128898","display_name":"Zhanhui Kang","orcid":"https://orcid.org/0009-0006-5151-4222"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanhui Kang","raw_affiliation_strings":["Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5102844742"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":6.1,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95431843,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2596","last_page":"2605"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9975000023841858,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.979200005531311,"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":0.7430704236030579},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33331459760665894}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7430704236030579},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33331459760665894}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3696410.3714663","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3696410.3714663","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714663","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3696410.3714663","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3696410.3714663","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714663","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G132187983","display_name":null,"funder_award_id":"62222215","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3841266055","display_name":null,"funder_award_id":"6222221","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4409657215.pdf","grobid_xml":"https://content.openalex.org/works/W4409657215.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W2018977290","https://openalex.org/W2117111450","https://openalex.org/W2171279286","https://openalex.org/W2605350416","https://openalex.org/W2783272285","https://openalex.org/W2884464324","https://openalex.org/W2902040508","https://openalex.org/W2963367478","https://openalex.org/W2965744319","https://openalex.org/W2984100107","https://openalex.org/W3087931390","https://openalex.org/W3100480425","https://openalex.org/W3119866685","https://openalex.org/W3133849783","https://openalex.org/W4287391717","https://openalex.org/W4389524555","https://openalex.org/W6601365666","https://openalex.org/W6630469555"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Recently,":[0],"many":[1],"efforts":[2],"have":[3,32],"been":[4],"devoted":[5],"to":[6,20,38,74,80,108,120,131,145,189],"building":[7],"effective":[8],"sequential":[9,30],"recommenders.Despite":[10],"their":[11,72,133],"effectiveness,":[12],"these":[13,177],"methods":[14],"typically":[15],"develop":[16],"a":[17,58,89,150],"single":[18],"model":[19,128],"serve":[21,146],"all":[22],"users.However,":[23],"our":[24,121],"empirical":[25],"studies":[26],"reveal":[27],"that":[28,161],"different":[29],"encoders":[31],"intrinsic":[33],"architectural":[34,135],"biases":[35,136],"and":[36,137,167],"tend":[37],"focus":[39],"on":[40,62,173,179],"specific":[41],"behavioral":[42,140],"patterns,":[43,78],"i.e.,":[44],"particular":[45],"frequency":[46,155],"range":[47],"of":[48,105,176],"user":[49,77,111,158],"behavior":[50,159],"sequences.For":[51],"example,":[52],"the":[53,67,103,114,118,174],"Self-Attention":[54],"module":[55],"is":[56],"essentially":[57],"low-pass":[59],"filter,":[60],"focusing":[61],"low-frequency":[63],"information":[64],"while":[65],"neglecting":[66],"high-frequency":[68],"details.This":[69],"evidently":[70],"limits":[71],"ability":[73],"capture":[75,138],"diverse":[76,139],"leading":[79],"suboptimal":[81],"recommendations.To":[82],"tackle":[83],"this":[84,180],"problem,":[85],"we":[86,123,148,182],"present":[87],"FamouSRec,":[88],"Frequency-Augmented":[90],"Mixture-of-Heterogeneous-Experts":[91],"Framework":[92],"for":[93,164],"personalized":[94],"Recommendations.Our":[95],"approach":[96],"builds":[97],"an":[98],"MoEbased":[99],"recommender":[100],"system,":[101],"integrating":[102],"strengths":[104],"various":[106,127],"experts":[107,125,144],"achieve":[109],"diversified":[110],"modeling.For":[112],"developing":[113],"MoE":[115],"framework,":[116,181],"as":[117],"key":[119],"approach,":[122],"instantiate":[124],"with":[126],"architectures,":[129],"aiming":[130],"leverage":[132],"inherent":[134],"patterns.For":[141],"selecting":[142],"appropriate":[143],"individuals,":[147],"introduce":[149],"frequency-augmented":[151],"router.It":[152],"first":[153],"identifies":[154],"components":[156],"in":[157],"sequences":[160],"are":[162],"suited":[163],"expert":[165,191],"encoding,":[166],"then":[168],"conducts":[169],"customized":[170],"routing":[171],"based":[172],"informativeness":[175],"components.Building":[178],"further":[183],"propose":[184],"two":[185],"novel":[186],"contrastive":[187],"tasks":[188],"enhance":[190]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}