{"id":"https://openalex.org/W4384652624","doi":"https://doi.org/10.1145/3539618.3591965","title":"Connecting Unseen Domains: Cross-Domain Invariant Learning in Recommendation","display_name":"Connecting Unseen Domains: Cross-Domain Invariant Learning in Recommendation","publication_year":2023,"publication_date":"2023-07-18","ids":{"openalex":"https://openalex.org/W4384652624","doi":"https://doi.org/10.1145/3539618.3591965"},"language":"en","primary_location":{"id":"doi:10.1145/3539618.3591965","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539618.3591965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101851341","display_name":"Yang Zhang","orcid":"https://orcid.org/0009-0006-4134-6253"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang Zhang","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0006-4134-6253","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007885672","display_name":"Yue Shen","orcid":"https://orcid.org/0000-0002-1046-9000"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yue Shen","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-1046-9000","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084313271","display_name":"Dong Wang","orcid":"https://orcid.org/0000-0003-2942-0220"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong Wang","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2942-0220","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053242349","display_name":"Jinjie Gu","orcid":"https://orcid.org/0000-0001-7596-4945"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinjie Gu","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7596-4945","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031338085","display_name":"Guannan Zhang","orcid":"https://orcid.org/0000-0002-7091-2318"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guannan Zhang","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7091-2318","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1894","last_page":"1898"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9990000128746033,"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":0.9990000128746033,"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":0.9976000189781189,"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":0.989300012588501,"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/leverage","display_name":"Leverage (statistics)","score":0.6948133111000061},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.6503391265869141},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6112197041511536},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5730786323547363},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.5506288409233093},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49825453758239746},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4765370786190033},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46207597851753235},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.44412845373153687},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.38131922483444214},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19876840710639954},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06654757261276245}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6948133111000061},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.6503391265869141},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6112197041511536},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5730786323547363},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.5506288409233093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49825453758239746},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4765370786190033},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46207597851753235},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.44412845373153687},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38131922483444214},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19876840710639954},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06654757261276245},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3539618.3591965","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539618.3591965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2054141820","https://openalex.org/W2114079787","https://openalex.org/W2512971201","https://openalex.org/W2796608345","https://openalex.org/W2798658180","https://openalex.org/W2809290718","https://openalex.org/W2963118547","https://openalex.org/W2971196067","https://openalex.org/W3028156525","https://openalex.org/W3087931390","https://openalex.org/W3098400049","https://openalex.org/W3099026360","https://openalex.org/W3171973478","https://openalex.org/W3190386329","https://openalex.org/W4213447687","https://openalex.org/W4290944323"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W2891261571","https://openalex.org/W4307930337","https://openalex.org/W3207081511","https://openalex.org/W4306674287","https://openalex.org/W4285606245","https://openalex.org/W4308482295","https://openalex.org/W3089674223","https://openalex.org/W3014026843","https://openalex.org/W4310030745"],"abstract_inverted_index":{"As":[0],"web":[1],"applications":[2],"continue":[3],"to":[4,48,50,148,152],"expand":[5],"and":[6,75,98,117,127,159,173],"diversify":[7],"their":[8],"services,":[9],"user":[10,110],"interactions":[11,111],"exist":[12],"in":[13,29,77,134],"different":[14],"scenarios.":[15],"To":[16],"leverage":[17],"this":[18,87],"wealth":[19],"of":[20,64,137,166],"information,":[21],"cross-domain":[22],"recommendation":[23],"(CDR)":[24],"has":[25],"gained":[26],"significant":[27],"attention":[28,46],"recent":[30,54],"years.":[31],"However,":[32],"existing":[33],"CDR":[34,97,172],"approaches":[35],"mostly":[36],"focus":[37],"on":[38,56,68,157],"information":[39],"transfer":[40],"between":[41],"observed":[42,153],"domains,":[43],"with":[44],"little":[45],"paid":[47],"generalizing":[49],"unseen":[51,82,150],"domains.":[52,154],"Although":[53],"research":[55],"invariant":[57,69,105,125],"learning":[58],"can":[59],"help":[60],"for":[61],"the":[62,81,124,128,164,167],"purpose":[63],"generalization,":[65],"relying":[66],"only":[67],"preference":[70,116,126,130],"may":[71],"be":[72],"overly":[73],"conservative":[74],"result":[76],"mediocre":[78],"performance":[79],"when":[80],"domain":[83,99,143,174],"shifts":[84],"slightly.":[85],"In":[86],"paper,":[88],"we":[89],"present":[90],"a":[91,102,135,141],"novel":[92,142],"framework":[93],"that":[94,109],"considers":[95],"both":[96,171],"generalization":[100,175],"through":[101],"united":[103],"causal":[104],"view.":[106],"We":[107],"assume":[108],"are":[112],"determined":[113],"by":[114],"domain-invariant":[115],"domain-specific":[118],"preference.":[119],"The":[120],"proposed":[121,168],"approach":[122,169],"differentiates":[123],"specific":[129],"from":[131],"observational":[132],"behaviors":[133],"way":[136],"adversarial":[138],"learning.":[139],"Additionally,":[140],"routing":[144],"module":[145],"is":[146],"designed":[147],"connect":[149],"domains":[151],"Extensive":[155],"experiments":[156],"public":[158],"industry":[160],"datasets":[161],"have":[162],"proved":[163],"effectiveness":[165],"under":[170],"settings.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}