{"id":"https://openalex.org/W4403221496","doi":"https://doi.org/10.1145/3640457.3688101","title":"Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation","display_name":"Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation","publication_year":2024,"publication_date":"2024-10-08","ids":{"openalex":"https://openalex.org/W4403221496","doi":"https://doi.org/10.1145/3640457.3688101"},"language":"en","primary_location":{"id":"doi:10.1145/3640457.3688101","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3640457.3688101","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688101","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"18th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688101","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071989106","display_name":"Xing Tang","orcid":"https://orcid.org/0000-0003-4360-0754"},"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":"Xing Tang","raw_affiliation_strings":["FiT,Tencent, China"],"raw_orcid":"https://orcid.org/0000-0003-4360-0754","affiliations":[{"raw_affiliation_string":"FiT,Tencent, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038484145","display_name":"Yang Qiao","orcid":"https://orcid.org/0009-0007-1668-213X"},"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":"Yang Qiao","raw_affiliation_strings":["FIT, Tencent, China"],"raw_orcid":"https://orcid.org/0009-0007-1668-213X","affiliations":[{"raw_affiliation_string":"FIT, Tencent, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079054140","display_name":"Fuyuan Lyu","orcid":"https://orcid.org/0000-0001-9345-1828"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Fuyuan Lyu","raw_affiliation_strings":["School of Computer Science, McGill University, Canada"],"raw_orcid":"https://orcid.org/0000-0001-9345-1828","affiliations":[{"raw_affiliation_string":"School of Computer Science, McGill University, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003106644","display_name":"Dugang Liu","orcid":"https://orcid.org/0000-0003-3612-709X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dugang Liu","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), China"],"raw_orcid":"https://orcid.org/0000-0003-3612-709X","affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083350101","display_name":"Xiuqiang He","orcid":"https://orcid.org/0000-0002-4115-8205"},"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":"Xiuqiang He","raw_affiliation_strings":["FiT,Tencent, China"],"raw_orcid":"https://orcid.org/0000-0002-4115-8205","affiliations":[{"raw_affiliation_string":"FiT,Tencent, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1197,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.93145512,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"329","last_page":"339"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9986000061035156,"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":0.9986000061035156,"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/T10028","display_name":"Topic Modeling","score":0.9904000163078308,"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":0.9882000088691711,"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":0.6889709830284119},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6606903672218323},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.5934808850288391},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.5425788164138794},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12009957432746887},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10191825032234192}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6889709830284119},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6606903672218323},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.5934808850288391},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5425788164138794},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12009957432746887},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10191825032234192},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3640457.3688101","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3640457.3688101","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688101","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"18th ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3640457.3688101","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3640457.3688101","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688101","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"18th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403221496.pdf"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W2190235285","https://openalex.org/W2798283910","https://openalex.org/W2809290718","https://openalex.org/W2913340405","https://openalex.org/W2951369132","https://openalex.org/W2963877604","https://openalex.org/W3034566015","https://openalex.org/W3035596828","https://openalex.org/W3087931390","https://openalex.org/W3098487628","https://openalex.org/W3156028762","https://openalex.org/W3172874292","https://openalex.org/W3187615801","https://openalex.org/W4220768948","https://openalex.org/W4256128330","https://openalex.org/W4284687367","https://openalex.org/W4290944246","https://openalex.org/W4292419518","https://openalex.org/W4312274013","https://openalex.org/W4378506818","https://openalex.org/W4380996048","https://openalex.org/W4382318707","https://openalex.org/W4384648854","https://openalex.org/W4385562485","https://openalex.org/W4385568136","https://openalex.org/W4386148469","https://openalex.org/W4386729349","https://openalex.org/W6600339963"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W3196817267","https://openalex.org/W1976600725"],"abstract_inverted_index":{"As":[0],"user":[1],"behaviors":[2],"become":[3],"complicated":[4],"on":[5,12,119,201,223],"business":[6],"platforms,":[7],"online":[8,220],"recommendations":[9],"focus":[10],"more":[11],"how":[13],"to":[14,23,63,147,162,195,213],"touch":[15],"the":[16,24,61,74,83,91,110,127,134,139,165,182,187,197,215,224],"core":[17,29,111],"conversions,":[18],"which":[19,81,171],"are":[20,31,211],"highly":[21],"related":[22],"interests":[25],"of":[26,85,217],"platforms.":[27],"These":[28],"conversions":[30,89],"usually":[32],"continuous":[33,93],"targets,":[34],"such":[35],"as":[36,60],"watch":[37],"time,":[38],"revenue,":[39],"and":[40,90,137,151,191,206],"so":[41],"on,":[42],"whose":[43],"predictions":[44],"can":[45,57,172],"be":[46,58],"enhanced":[47],"by":[48],"previous":[49],"discrete":[50,78,88],"conversion":[51,79],"actions.":[52],"Therefore,":[53],"multi-task":[54],"learning":[55],"(MTL)":[56],"adopted":[59],"paradigm":[62],"learn":[64],"these":[65,169],"hybrid":[66,98,131],"targets.":[67],"However,":[68],"existing":[69],"works":[70],"mainly":[71],"emphasize":[72],"investigating":[73],"sequential":[75],"dependence":[76,86,103,150],"among":[77,168],"actions,":[80],"neglects":[82],"complexity":[84],"between":[87,186],"final":[92,188],"conversion.":[94],"Moreover,":[95,219],"simultaneously":[96],"optimizing":[97],"tasks":[99,194],"with":[100,130],"stronger":[101],"task":[102,113,149,161,176,190],"will":[104],"suffer":[105],"from":[106],"volatile":[107],"issues":[108],"where":[109],"regression":[112,189],"might":[114],"have":[115],"a":[116],"larger":[117],"influence":[118],"other":[120,192],"tasks.":[121],"In":[122],"this":[123],"paper,":[124],"we":[125,155],"study":[126],"MTL":[128],"problem":[129],"targets":[132],"for":[133,159],"first":[135],"time":[136],"propose":[138],"model":[140,232],"named":[141],"Hybrid":[142],"Targets":[143],"Learning":[144],"Network":[145],"(HTLNet)":[146],"explore":[148,174],"enhance":[152,196],"optimization.":[153,198],"Specifically,":[154],"introduce":[156],"label":[157,166],"embedding":[158],"each":[160],"explicitly":[163],"transfer":[164],"information":[167],"tasks,":[170],"effectively":[173],"logical":[175],"dependence.":[177],"We":[178],"also":[179,228],"further":[180],"design":[181],"gradient":[183],"adjustment":[184],"regime":[185],"classification":[193],"Extensive":[199],"experiments":[200],"two":[202],"offline":[203],"public":[204],"datasets":[205],"one":[207],"real-world":[208],"industrial":[209],"dataset":[210],"conducted":[212],"validate":[214],"effectiveness":[216],"HTLNet.":[218],"A/B":[221],"tests":[222],"financial":[225],"recommender":[226],"system":[227],"show":[229],"that":[230],"our":[231],"has":[233],"improved":[234],"significantly.":[235],"Our":[236],"implementation":[237],"is":[238],"available":[239],"here1.":[240]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}