{"id":"https://openalex.org/W4221030716","doi":"https://doi.org/10.1145/3522672","title":"Revisiting Negative Sampling vs. Non-sampling in Implicit Recommendation","display_name":"Revisiting Negative Sampling vs. Non-sampling in Implicit Recommendation","publication_year":2022,"publication_date":"2022-03-25","ids":{"openalex":"https://openalex.org/W4221030716","doi":"https://doi.org/10.1145/3522672"},"language":"en","primary_location":{"id":"doi:10.1145/3522672","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3522672","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3522672","source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3522672","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100348803","display_name":"Chong Chen","orcid":"https://orcid.org/0000-0003-4751-1134"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chong Chen","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101524043","display_name":"Weizhi Ma","orcid":"https://orcid.org/0000-0001-5604-7527"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weizhi Ma","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100402996","display_name":"Min Zhang","orcid":"https://orcid.org/0000-0003-3158-1920"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Zhang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100424699","display_name":"Chenyang Wang","orcid":"https://orcid.org/0000-0002-3490-3385"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyang Wang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100668121","display_name":"Yiqun Liu","orcid":"https://orcid.org/0000-0002-0140-4512"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqun Liu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100760812","display_name":"Shaoping Ma","orcid":"https://orcid.org/0000-0002-8762-8268"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoping Ma","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100348803"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":21.3625,"has_fulltext":true,"cited_by_count":74,"citation_normalized_percentile":{"value":0.99460088,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"41","issue":"1","first_page":"1","last_page":"25"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9983000159263611,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9922000169754028,"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/sampling","display_name":"Sampling (signal processing)","score":0.8213968276977539},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7213373780250549},{"id":"https://openalex.org/keywords/experience-sampling-method","display_name":"Experience sampling method","score":0.7002111673355103},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5395153760910034},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43412837386131287},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.381137490272522},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33304762840270996},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.152369886636734},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.10984805226325989},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08194246888160706}],"concepts":[{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.8213968276977539},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7213373780250549},{"id":"https://openalex.org/C65499552","wikidata":"https://www.wikidata.org/wiki/Q5421061","display_name":"Experience sampling method","level":2,"score":0.7002111673355103},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5395153760910034},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43412837386131287},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.381137490272522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33304762840270996},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.152369886636734},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.10984805226325989},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08194246888160706},{"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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3522672","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3522672","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3522672","source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3522672","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3522672","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3522672","source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3085993365","display_name":null,"funder_award_id":"(Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3379573397","display_name":null,"funder_award_id":"U21B2026","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4535293930","display_name":null,"funder_award_id":"U21B2026, 62002191","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4221030716.pdf","grobid_xml":"https://content.openalex.org/works/W4221030716.grobid-xml"},"referenced_works_count":76,"referenced_works":["https://openalex.org/W91851626","https://openalex.org/W178169250","https://openalex.org/W1690919088","https://openalex.org/W1888005072","https://openalex.org/W1976999215","https://openalex.org/W1994389483","https://openalex.org/W2054141820","https://openalex.org/W2102035799","https://openalex.org/W2146241755","https://openalex.org/W2154851992","https://openalex.org/W2512971201","https://openalex.org/W2531563875","https://openalex.org/W2565948352","https://openalex.org/W2575006718","https://openalex.org/W2604272474","https://openalex.org/W2619206542","https://openalex.org/W2741249238","https://openalex.org/W2742272831","https://openalex.org/W2767980859","https://openalex.org/W2768762802","https://openalex.org/W2795199972","https://openalex.org/W2799079108","https://openalex.org/W2807021761","https://openalex.org/W2886144305","https://openalex.org/W2900229157","https://openalex.org/W2900300695","https://openalex.org/W2905267911","https://openalex.org/W2911465377","https://openalex.org/W2913077324","https://openalex.org/W2913106281","https://openalex.org/W2913415152","https://openalex.org/W2914721378","https://openalex.org/W2914865568","https://openalex.org/W2944441143","https://openalex.org/W2945623882","https://openalex.org/W2945827670","https://openalex.org/W2951611179","https://openalex.org/W2954123367","https://openalex.org/W2957191877","https://openalex.org/W2962756421","https://openalex.org/W2962992837","https://openalex.org/W2963485453","https://openalex.org/W2964086597","https://openalex.org/W2973172293","https://openalex.org/W2999649805","https://openalex.org/W3011809564","https://openalex.org/W3012780388","https://openalex.org/W3012952868","https://openalex.org/W3035566692","https://openalex.org/W3080456792","https://openalex.org/W3081170586","https://openalex.org/W3083784942","https://openalex.org/W3088777230","https://openalex.org/W3095727144","https://openalex.org/W3100278010","https://openalex.org/W3100848837","https://openalex.org/W3101023724","https://openalex.org/W3101063193","https://openalex.org/W3101951402","https://openalex.org/W3102030627","https://openalex.org/W3104097132","https://openalex.org/W3105114834","https://openalex.org/W3106445281","https://openalex.org/W3122730565","https://openalex.org/W3156135334","https://openalex.org/W3172854437","https://openalex.org/W3178476575","https://openalex.org/W3201053014","https://openalex.org/W4212937970","https://openalex.org/W4213069590","https://openalex.org/W4246698901","https://openalex.org/W4301312111","https://openalex.org/W4301409532","https://openalex.org/W6758918355","https://openalex.org/W6766152879","https://openalex.org/W6783646676"],"related_works":["https://openalex.org/W2039864646","https://openalex.org/W2809023326","https://openalex.org/W2389214306","https://openalex.org/W4298005780","https://openalex.org/W4310208846","https://openalex.org/W2965083567","https://openalex.org/W4235240664","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2889616422"],"abstract_inverted_index":{"Recommendation":[0],"systems":[1],"play":[2],"an":[3],"important":[4],"role":[5,134],"in":[6,143,177],"alleviating":[7],"the":[8,32,50,70,90,95,111,133,151,170,214],"information":[9],"overload":[10],"issue.":[11],"Generally,":[12],"a":[13,160],"recommendation":[14,142,166,194],"model":[15],"is":[16,197],"trained":[17],"to":[18,105,192,203,207],"discern":[19],"between":[20],"positive":[21,38],"(liked)":[22],"and":[23,74,117,138,156,175,216,221,223,228],"negative":[24,42,56,71,81,115,136,154,173,186,219],"(disliked)":[25],"instances":[26,39,43,82],"for":[27,108,140,199],"each":[28],"user.":[29],"However,":[30],"under":[31],"open-world":[33],"assumption,":[34],"there":[35],"are":[36,103,233],"only":[37],"but":[40],"no":[41],"from":[44,83],"users\u2019":[45],"implicit":[46,141],"feedback,":[47],"which":[48],"poses":[49],"imbalanced":[51],"learning":[52,64,101,209],"challenge":[53],"of":[54,63,114,135,153,163,172,218],"lacking":[55],"samples.":[57],"To":[58,126],"address":[59],"this,":[60],"two":[61],"types":[62],"strategies":[65,102],"have":[66],"been":[67,121,189],"proposed":[68],"before,":[69],"sampling":[72,116,137,155,174,187,201,220],"strategy":[73,79,92],"non-sampling":[75,91,118,139,176,208,222],"strategy.":[76],"The":[77],"first":[78,148],"samples":[80],"missing":[84,96],"data":[85,97],"(i.e.,":[86],"unlabeled":[87],"data),":[88],"while":[89],"regards":[93],"all":[94],"as":[98],"negative.":[99],"Although":[100],"known":[104],"be":[106],"essential":[107],"algorithm":[109],"performance,":[110],"in-depth":[112],"comparison":[113],"has":[119,188],"not":[120],"sufficiently":[122],"explored":[123],"by":[124],"far.":[125],"bridge":[127],"this":[128,144],"gap,":[129],"we":[130,147,168,212],"systematically":[131],"analyze":[132],"work.":[145],"Specifically,":[146],"theoretically":[149],"revisit":[150],"objection":[152],"non-sampling.":[157],"Then,":[158],"with":[159],"careful":[161],"setup":[162],"various":[164],"representative":[165],"methods,":[167],"explore":[169],"performance":[171,206],"different":[178],"scenarios.":[179],"Our":[180],"results":[181],"empirically":[182],"show":[183,204],"that":[184,232],"although":[185],"widely":[190],"applied":[191],"recent":[193],"models,":[195],"it":[196],"non-trivial":[198],"uniform":[200],"methods":[202],"comparable":[205],"methods.":[210],"Finally,":[211],"discuss":[213],"scalability":[215],"complexity":[217],"present":[224],"some":[225],"open":[226],"problems":[227],"future":[229],"research":[230],"topics":[231],"worth":[234],"being":[235],"further":[236],"explored.":[237]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":46},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":10}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}