{"id":"https://openalex.org/W4386875129","doi":"https://doi.org/10.1145/3583780.3614657","title":"An Unified Search and Recommendation Foundation Model for Cold-Start Scenario","display_name":"An Unified Search and Recommendation Foundation Model for Cold-Start Scenario","publication_year":2023,"publication_date":"2023-10-21","ids":{"openalex":"https://openalex.org/W4386875129","doi":"https://doi.org/10.1145/3583780.3614657"},"language":"en","primary_location":{"id":"doi:10.1145/3583780.3614657","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583780.3614657","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2309.08939","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045499946","display_name":"Yuqi Gong","orcid":"https://orcid.org/0009-0000-6794-1604"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yuqi Gong","raw_affiliation_strings":["Ant Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080106267","display_name":"Xichen Ding","orcid":"https://orcid.org/0009-0003-5649-058X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xichen Ding","raw_affiliation_strings":["Ant Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087981910","display_name":"Yehui Su","orcid":"https://orcid.org/0009-0002-1006-2072"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yehui Su","raw_affiliation_strings":["Ant Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019753041","display_name":"Kaiming Shen","orcid":"https://orcid.org/0009-0001-4742-210X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaiming Shen","raw_affiliation_strings":["Ant Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Ant Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023862460","display_name":"Zhongyi Liu","orcid":"https://orcid.org/0000-0001-9478-8107"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhongyi Liu","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"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"],"affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5045499946"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.6533,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.94429234,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4595","last_page":"4601"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9979000091552734,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9979000091552734,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9969000220298767,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9950000047683716,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8483136892318726},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5297874808311462},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5060271620750427},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.49304649233818054},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.46841946244239807},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.46275898814201355},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4474230408668518},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.44391798973083496},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40194135904312134},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32093727588653564}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8483136892318726},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5297874808311462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5060271620750427},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.49304649233818054},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.46841946244239807},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.46275898814201355},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4474230408668518},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.44391798973083496},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40194135904312134},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32093727588653564},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3583780.3614657","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583780.3614657","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2309.08939","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.08939","pdf_url":"https://arxiv.org/pdf/2309.08939","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2309.08939","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.08939","pdf_url":"https://arxiv.org/pdf/2309.08939","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.49000000953674316,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386875129.pdf"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1731081199","https://openalex.org/W2740070748","https://openalex.org/W2809290718","https://openalex.org/W2810397803","https://openalex.org/W2884789176","https://openalex.org/W2896457183","https://openalex.org/W2913340405","https://openalex.org/W2951661358","https://openalex.org/W3002414756","https://openalex.org/W3087931390","https://openalex.org/W3104763847","https://openalex.org/W3123878450","https://openalex.org/W3203749733","https://openalex.org/W3208380962","https://openalex.org/W3209943551","https://openalex.org/W4212836229","https://openalex.org/W4220907840","https://openalex.org/W4224313506","https://openalex.org/W4280586754","https://openalex.org/W4285294723","https://openalex.org/W4290943593","https://openalex.org/W4292779060","https://openalex.org/W4297969478","https://openalex.org/W4303443398","https://openalex.org/W4306317361","https://openalex.org/W4322718191","https://openalex.org/W4362515116","https://openalex.org/W4377130978","https://openalex.org/W4385568359","https://openalex.org/W6637618735"],"related_works":["https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W2056712470","https://openalex.org/W3125580266","https://openalex.org/W4317039510","https://openalex.org/W4238861846","https://openalex.org/W790944756"],"abstract_inverted_index":{"In":[0],"modern":[1],"commercial":[2],"search":[3,72,123],"engines":[4],"and":[5,39,49,73,93,106,117,124,186],"recommendation":[6,74,125,185],"systems,":[7],"data":[8],"from":[9,121],"multiple":[10,37,122],"domains":[11],"is":[12],"available":[13],"to":[14,32,42,88,97,111,135,148],"jointly":[15,129],"train":[16,22],"the":[17,26,34,44,56,99,113,137,143,153],"multi-domain":[18,23,138],"model.":[19,140],"Traditional":[20],"methods":[21],"models":[24],"in":[25,152,175],"multi-task":[27],"setting,":[28],"with":[29,130],"shared":[30],"parameters":[31,41],"learn":[33,43],"similarity":[35],"of":[36,46,52,58,115],"tasks,":[38],"task-specific":[40,107],"divergence":[45],"features,":[47,92],"labels,":[48],"sample":[50],"distributions":[51],"individual":[53],"tasks.":[54,75],"With":[55],"development":[57],"large":[59],"language":[60],"models,":[61],"LLM":[62,87],"can":[63],"extract":[64,89],"global":[65],"domain-invariant":[66],"text":[67,104],"features":[68,105,110],"that":[69],"serve":[70],"both":[71],"We":[76,141],"propose":[77],"a":[78],"novel":[79],"framework":[80],"called":[81],"S&R":[82,144,167],"Multi-Domain":[83,145,168],"Foundation,":[84],"which":[85,156],"uses":[86],"domain":[90,102],"invariant":[91,103],"Aspect":[94],"Gating":[95],"Fusion":[96],"merge":[98],"ID":[100],"feature,":[101],"heterogeneous":[108],"sparse":[109],"obtain":[112,136],"representations":[114],"query":[116,184],"item.":[118],"Additionally,":[119],"samples":[120],"scenarios":[126,151],"are":[127],"trained":[128],"Domain":[131],"Adaptive":[132],"Multi-Task":[133],"module":[134],"foundation":[139,146],"apply":[142],"model":[147,170],"cold":[149],"start":[150],"pretrain-finetune":[154],"manner,":[155],"achieves":[157],"better":[158],"performance":[159],"than":[160],"other":[161],"SOTA":[162],"transfer":[163],"learning":[164],"methods.":[165],"The":[166],"Foundation":[169],"has":[171],"been":[172],"successfully":[173],"deployed":[174],"Alipay":[176],"Mobile":[177],"Application's":[178],"online":[179],"services,":[180],"such":[181],"as":[182],"content":[183],"service":[187],"card":[188],"recommendation,":[189],"etc.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":12}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
