{"id":"https://openalex.org/W4407953286","doi":"https://doi.org/10.1145/3701551.3703539","title":"AMLCDR: An Adaptive Meta-Learning Model for Cross-Domain Recommendation by Aligning Preference Distributions","display_name":"AMLCDR: An Adaptive Meta-Learning Model for Cross-Domain Recommendation by Aligning Preference Distributions","publication_year":2025,"publication_date":"2025-02-26","ids":{"openalex":"https://openalex.org/W4407953286","doi":"https://doi.org/10.1145/3701551.3703539"},"language":"en","primary_location":{"id":"doi:10.1145/3701551.3703539","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3701551.3703539","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining","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/A5101382733","display_name":"Fanqi Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fanqi Meng","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015455705","display_name":"Zhiyuan Zhang","orcid":"https://orcid.org/0000-0002-6752-0794"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Zhang","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101382733"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":6.9916,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95593852,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"606","last_page":"615"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9883999824523926,"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/T10028","display_name":"Topic Modeling","score":0.9814000129699707,"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":0.6982866525650024},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.6767805218696594},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5655192732810974},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43912622332572937},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.42262423038482666},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34352409839630127},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12353962659835815},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1107165515422821},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09271174669265747},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.06342947483062744}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6982866525650024},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.6767805218696594},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5655192732810974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43912622332572937},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.42262423038482666},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34352409839630127},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12353962659835815},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1107165515422821},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09271174669265747},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.06342947483062744},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3701551.3703539","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3701551.3703539","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1502375784","https://openalex.org/W2007658183","https://openalex.org/W2027731328","https://openalex.org/W2054141820","https://openalex.org/W2069870183","https://openalex.org/W2117420919","https://openalex.org/W2512971201","https://openalex.org/W2593768305","https://openalex.org/W2605350416","https://openalex.org/W2723293840","https://openalex.org/W2740605635","https://openalex.org/W2884771968","https://openalex.org/W2895281799","https://openalex.org/W2904156528","https://openalex.org/W2904209271","https://openalex.org/W2914294271","https://openalex.org/W2962823940","https://openalex.org/W2963602998","https://openalex.org/W2987219395","https://openalex.org/W2996891863","https://openalex.org/W3021632667","https://openalex.org/W3028156525","https://openalex.org/W3041133507","https://openalex.org/W3097173804","https://openalex.org/W3099026360","https://openalex.org/W3106251865","https://openalex.org/W3155450594","https://openalex.org/W3170587616","https://openalex.org/W3189951784","https://openalex.org/W3209185641","https://openalex.org/W3209943551","https://openalex.org/W3210022786","https://openalex.org/W3215053434","https://openalex.org/W4200297316","https://openalex.org/W4283324687","https://openalex.org/W4285688121","https://openalex.org/W4287815740","https://openalex.org/W4297971002","https://openalex.org/W4384887418","https://openalex.org/W4388532091"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"The":[0,34,131],"issue":[1],"of":[2,12,36,78,173,185],"data":[3,56,85,186],"sparsity":[4],"poses":[5],"a":[6,42,51,67,121,134,144,156,177],"formidable":[7],"challenge":[8],"in":[9,22,30,45,107,189,205],"the":[10,17,23,31,46,75,83,89,96,104,108,112,149,171,183],"field":[11],"recommender":[13],"systems.":[14],"Encouragingly,":[15],"leveraging":[16],"interactions":[18],"among":[19],"overlapping":[20],"users":[21],"source":[24,90],"domain":[25,91,110,157,190],"can":[26],"enhance":[27],"item":[28,105],"recommendation":[29,48,113,195],"target":[32,93,109],"domain.":[33,94],"transfer":[35,61,69,145],"user":[37,98,140,150,162],"preferences":[38],"across":[39],"domains":[40],"is":[41],"crucial":[43],"concern":[44],"cross-domain":[47,76,194],"and":[49,81,92,111,142],"represents":[50],"hopeful":[52],"method":[53,123,132],"to":[54,147,160,169],"address":[55],"sparsity.":[57],"Most":[58],"existing":[59],"methods":[60,72],"users'":[62],"preference":[63,68,79,151,163],"information":[64],"by":[65,175],"building":[66],"network.":[70],"These":[71],"focus":[73],"on":[74],"mapping":[77],"features":[80],"ignore":[82],"inherent":[84],"distribution":[86,187],"differences":[87],"between":[88],"Consequently,":[95],"mapped":[97],"embeddings":[99,106],"do":[100],"not":[101],"align":[102,161],"with":[103],"quality":[114],"decreases.":[115],"On":[116],"this":[117],"basis,":[118],"we":[119],"propose":[120],"new":[122],"called":[124],"Adaptive":[125],"Meta-Learning":[126],"for":[127,137],"Cross-Domain":[128],"Recommendation":[129],"(AMLCDR).":[130],"includes":[133],"meta-learning":[135],"network":[136,146,159],"fully":[138],"extracting":[139],"characteristics":[141],"generating":[143],"reduce":[148],"loss,":[152],"as":[153,155],"well":[154],"adaptation":[158],"distributions.":[164],"We":[165,181],"perform":[166],"comprehensive":[167],"experiments":[168],"assess":[170],"efficacy":[172],"AMLCDR":[174,201],"utilizing":[176],"substantial":[178],"real-world":[179],"dataset.":[180],"validate":[182],"effectiveness":[184],"alignment":[188],"adaptation.":[191],"For":[192],"diverse":[193],"tasks":[196],"under":[197],"different":[198],"start":[199],"conditions,":[200],"outperforms":[202],"state-of-the-art":[203],"models":[204],"multiple":[206],"evaluation":[207],"metrics.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
