{"id":"https://openalex.org/W3216317163","doi":"https://doi.org/10.1145/3485447.3511971","title":"Learning Explicit User Interest Boundary for Recommendation","display_name":"Learning Explicit User Interest Boundary for Recommendation","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W3216317163","doi":"https://doi.org/10.1145/3485447.3511971","mag":"3216317163"},"language":"en","primary_location":{"id":"doi:10.1145/3485447.3511971","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3485447.3511971","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3485447.3511971","source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 2022","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3485447.3511971","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079632234","display_name":"Jianhuan Zhuo","orcid":"https://orcid.org/0000-0002-0449-6459"},"institutions":[{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhuan Zhuo","raw_affiliation_strings":["Institute of Information Engineering, Chinese Academy of Sciences, China and School of Cyber Security, University of Chinese Academy of Sciences, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Engineering, Chinese Academy of Sciences, China and School of Cyber Security, University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016532375","display_name":"Qiannan Zhu","orcid":"https://orcid.org/0000-0002-9502-478X"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiannan Zhu","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, China and Beijing Key Laboratory of Big Data Management and Analysis Methods, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, China and Beijing Key Laboratory of Big Data Management and Analysis Methods, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056000853","display_name":"Yinliang Yue","orcid":"https://orcid.org/0000-0002-8417-2234"},"institutions":[{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinliang Yue","raw_affiliation_strings":["Institute of Information Engineering, Chinese Academy of Sciences, China and School of Cyber Security, University of Chinese Academy of Sciences, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Engineering, Chinese Academy of Sciences, China and School of Cyber Security, University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109974111","display_name":"Yuhong Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhong Zhao","raw_affiliation_strings":["Institute of Information Engineering, Chinese Academy of Sciences, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Engineering, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"193","last_page":"202"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9837999939918518,"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/pointwise","display_name":"Pointwise","score":0.9396531581878662},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.904721736907959},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7623544335365295},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.7064992189407349},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.6277239322662354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6014058589935303},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5270904302597046},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4980497360229492},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.49715927243232727},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.45684659481048584},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.43811458349227905},{"id":"https://openalex.org/keywords/decision-boundary","display_name":"Decision boundary","score":0.4101749658584595},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40250635147094727},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36536070704460144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36332961916923523},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3071572780609131},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.06020364165306091}],"concepts":[{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.9396531581878662},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.904721736907959},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7623544335365295},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7064992189407349},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.6277239322662354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6014058589935303},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5270904302597046},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4980497360229492},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.49715927243232727},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.45684659481048584},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.43811458349227905},{"id":"https://openalex.org/C42023084","wikidata":"https://www.wikidata.org/wiki/Q5249231","display_name":"Decision boundary","level":3,"score":0.4101749658584595},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40250635147094727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36536070704460144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36332961916923523},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3071572780609131},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.06020364165306091},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3485447.3511971","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3485447.3511971","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3485447.3511971","source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 2022","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2111.11026","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.11026","pdf_url":"https://arxiv.org/pdf/2111.11026","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3216317163","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2111.11026","pdf_url":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2111.11026","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2111.11026","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.1145/3485447.3511971","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3485447.3511971","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3485447.3511971","source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 2022","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3216317163.pdf","grobid_xml":"https://content.openalex.org/works/W3216317163.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W1976999215","https://openalex.org/W1984290568","https://openalex.org/W2036536766","https://openalex.org/W2121949863","https://openalex.org/W2140310134","https://openalex.org/W2143331230","https://openalex.org/W2146502635","https://openalex.org/W2154399841","https://openalex.org/W2219888463","https://openalex.org/W2512971201","https://openalex.org/W2604397568","https://openalex.org/W2604433096","https://openalex.org/W2605350416","https://openalex.org/W2606864227","https://openalex.org/W2619206542","https://openalex.org/W2766016831","https://openalex.org/W2768012150","https://openalex.org/W2788456731","https://openalex.org/W2796816447","https://openalex.org/W2798868970","https://openalex.org/W2905267911","https://openalex.org/W2906684937","https://openalex.org/W2950491307","https://openalex.org/W2966799427","https://openalex.org/W2970971581","https://openalex.org/W2972734859","https://openalex.org/W2997457842","https://openalex.org/W2998508934","https://openalex.org/W2999649805","https://openalex.org/W3034303554","https://openalex.org/W3045200674","https://openalex.org/W3098649723","https://openalex.org/W3101023724","https://openalex.org/W3103931423","https://openalex.org/W3124009622","https://openalex.org/W3130313700","https://openalex.org/W3197404256","https://openalex.org/W3203926743","https://openalex.org/W3210547226","https://openalex.org/W4210880854","https://openalex.org/W4251597219","https://openalex.org/W4297971002"],"related_works":[],"abstract_inverted_index":{"The":[0,38],"core":[1],"objective":[2],"of":[3,78,168,178],"modelling":[4],"recommender":[5],"systems":[6],"from":[7,83],"implicit":[8],"feedback":[9],"is":[10,49,144,154],"to":[11,91,98,121,174],"maximize":[12],"the":[13,20,33,36,59,66,72,76,123,133,139,149,169,172,176,195,215],"positive":[14,140],"sample":[15,22,43],"score":[16,23,68,116,143,153],"sp":[17],"and":[18,35,53,127,148,171,192,229],"minimize":[19],"negative":[21,150],"sn,":[24],"which":[25,48],"can":[26,186],"usually":[27],"be":[28],"summarized":[29],"into":[30],"two":[31],"paradigms:":[32],"pointwise":[34,39,170,217],"pairwise.":[37],"approaches":[40,74,88],"fit":[41],"each":[42,119],"with":[44,135,225],"its":[45],"label":[46],"individually,":[47],"flexible":[50],"in":[51,104],"weighting":[52],"sampling":[54,201],"on":[55,212],"instance-level":[56],"but":[57,81,221],"ignores":[58],"inherent":[60],"ranking":[61,77],"property.":[62],"By":[63],"qualitatively":[64],"minimizing":[65],"relative":[67],"sn":[69],"\u2212":[70],"sp,":[71],"pairwise":[73,136,173,219],"capture":[75],"samples":[79,130,141,151],"naturally":[80],"suffer":[82],"training":[84,196],"efficiency.":[85],"Additionally,":[86],"both":[87],"are":[89,102],"hard":[90],"explicitly":[92],"provide":[93,187],"a":[94,165,188],"personalized":[95,189],"decision":[96,190],"boundary":[97,134,191],"determine":[99],"if":[100],"users":[101],"interested":[103],"items":[105],"unseen.":[106],"To":[107],"address":[108],"those":[109],"issues,":[110],"we":[111,181],"innovatively":[112],"introduce":[113],"an":[114],"auxiliary":[115],"bu":[117,147],"for":[118],"user":[120],"represent":[122],"User":[124],"Interest":[125],"Boundary(UIB)":[126],"individually":[128],"penalize":[129],"that":[131,183,206],"cross":[132],"paradigms,":[137],"i.e.,":[138],"whose":[142,152],"lower":[145],"than":[146,156],"higher":[155],"bu.":[157],"In":[158],"this":[159],"way,":[160],"our":[161,184,207],"approach":[162,185,208],"successfully":[163],"achieves":[164,209],"hybrid":[166],"loss":[167,227],"combine":[175],"advantages":[177],"both.":[179],"Analytically,":[180],"show":[182,205],"significantly":[193],"improve":[194],"efficiency":[197],"without":[198],"any":[199],"special":[200],"strategy.":[202],"Extensive":[203],"results":[204],"significant":[210],"improvements":[211],"not":[213],"only":[214],"classical":[216],"or":[218],"models":[220,224],"also":[222],"state-of-the-art":[223],"complex":[226],"function":[228],"complicated":[230],"feature":[231],"encoding.":[232]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}