{"id":"https://openalex.org/W7155851662","doi":"https://doi.org/10.1145/3774904.3792253","title":"Bridging Explicit and Implicit Intent: Unified Interest Generative Method for Joint Search-Recommendation Modeling","display_name":"Bridging Explicit and Implicit Intent: Unified Interest Generative Method for Joint Search-Recommendation Modeling","publication_year":2026,"publication_date":"2026-04-12","ids":{"openalex":"https://openalex.org/W7155851662","doi":"https://doi.org/10.1145/3774904.3792253"},"language":null,"primary_location":{"id":"doi:10.1145/3774904.3792253","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792253","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774904.3792253","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053595500","display_name":"Dongliang Liao","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongliang Liao","raw_affiliation_strings":["South China University of Technology, Guangzhou, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0003-4761-5208","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101528191","display_name":"Chenxing Wang","orcid":"https://orcid.org/0000-0003-4096-7972"},"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":"Chenxing Wang","raw_affiliation_strings":["Tencent Inc., guangzhou, guangdong, China"],"raw_orcid":"https://orcid.org/0000-0003-4096-7972","affiliations":[{"raw_affiliation_string":"Tencent Inc., guangzhou, guangdong, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101296394","display_name":"Zeng YaWen","orcid":"https://orcid.org/0000-0003-1908-1157"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yawen Zeng","raw_affiliation_strings":["South China University of Technology, Guangzhou, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0003-1908-1157","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":0.67632343,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6103","last_page":"6113"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.8708999752998352,"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":0.8708999752998352,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.026000000536441803,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.009100000374019146,"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/bridging","display_name":"Bridging (networking)","score":0.6687999963760376},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.48330000042915344},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4747999906539917},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4350999891757965},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4004000127315521},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.3903000056743622},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.37220001220703125},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3716999888420105},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3684000074863434}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8090999722480774},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.6687999963760376},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.48330000042915344},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4747999906539917},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43959999084472656},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4350999891757965},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4004000127315521},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3903000056743622},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38420000672340393},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3833000063896179},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.37220001220703125},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3716999888420105},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3684000074863434},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.36820000410079956},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.36660000681877136},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.3375999927520752},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.32350000739097595},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.30630001425743103},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29739999771118164},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.26010000705718994},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774904.3792253","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792253","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3774904.3792253","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792253","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.45770102739334106}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2101409192","https://openalex.org/W2723293840","https://openalex.org/W2809290718","https://openalex.org/W2962686347","https://openalex.org/W2984100107","https://openalex.org/W2997864604","https://openalex.org/W3087931390","https://openalex.org/W3094605108","https://openalex.org/W3203749733","https://openalex.org/W4212836229","https://openalex.org/W4220907840","https://openalex.org/W4220974940","https://openalex.org/W4224313506","https://openalex.org/W4306317239","https://openalex.org/W4377130978","https://openalex.org/W4385568157","https://openalex.org/W4387854274","https://openalex.org/W4414034997"],"related_works":[],"abstract_inverted_index":{"Search":[0],"and":[1,32,59,105,118,146,167],"Recommendation":[2],"(S&R)":[3],"are":[4],"core":[5],"information":[6],"access":[7],"channels":[8],"on":[9,74,162],"modern":[10],"multi-scenario":[11],"platforms.":[12],"Existing":[13],"joint":[14,178],"S&R":[15,45,179,189],"models":[16],"face":[17],"two":[18,81,163],"critical":[19],"challenges:":[20],"(1)":[21],"cross-scenario":[22,112],"interest":[23,41,77],"inconsistency,":[24],"failing":[25],"to":[26,55,95,186],"unify":[27],"explicit":[28,117],"search":[29],"intent":[30,35],"(queries)":[31],"implicit":[33,119],"recommendation":[34],"(behavioral":[36],"interactions)":[37],"into":[38],"coherent":[39],"user":[40,76,98],"representations;":[42],"(2)":[43],"severe":[44],"trade-off,":[46],"where":[47],"enhancing":[48],"one":[49],"task":[50],"degrades":[51],"the":[52,188],"other":[53],"due":[54],"static":[56,128],"knowledge":[57,145],"sharing":[58],"unbalanced":[60],"feature":[61],"utilization.":[62],"To":[63],"address":[64],"these":[65],"issues,":[66],"we":[67],"propose":[68],"MinSAR,":[69],"a":[70,84,101],"novel":[71],"framework":[72],"focusing":[73],"cross-S&R":[75,143],"consistency.":[78],"It":[79],"integrates":[80],"key":[82],"innovations:":[83],"Unified":[85],"Interest":[86],"Generation":[87],"(UIG)":[88],"module":[89],"using":[90],"Vector":[91],"Quantized-Variational":[92],"Autoencoder":[93],"(VQ-VAE)":[94],"fuse":[96],"long-term":[97],"preferences":[99],"(via":[100],"user-specific":[102],"memory":[103],"network)":[104],"dynamic":[106],"short-term":[107],"contextual":[108],"behaviors,":[109],"generating":[110],"compact":[111],"latent":[113],"representations":[114],"that":[115],"bridge":[116],"intents.":[120],"Additionally,":[121],"an":[122],"Interest-Guided":[123],"Attention":[124],"Expert":[125],"Network":[126],"replaces":[127],"multi-task":[129],"gating":[130],"with":[131],"intent-aware":[132],"weight":[133],"allocation.":[134],"Guided":[135],"by":[136],"UIG's":[137],"unified":[138],"interest,":[139],"it":[140],"dynamically":[141],"balances":[142],"shared":[144],"task-specific":[147],"expertise":[148],"(semantic":[149],"matching":[150],"for":[151,155],"search,":[152],"collaborative":[153],"filtering":[154],"recommendation),":[156],"mitigating":[157],"inter-task":[158],"conflicts.":[159],"Extensive":[160],"experiments":[161],"real-world":[164],"datasets":[165],"(KuaiSAR":[166],"Amazon":[168],"Kindle":[169],"Store)":[170],"against":[171],"13":[172],"baselines":[173],"show":[174],"MinSAR":[175],"outperforms":[176],"state-of-the-art":[177],"models.":[180],"Further":[181],"analysis":[182],"confirms":[183],"its":[184],"ability":[185],"eliminate":[187],"performance":[190],"trade-off.":[191]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-28T00:00:00"}
