{"id":"https://openalex.org/W3187508330","doi":"https://doi.org/10.1145/3460231.3474274","title":"Debiased Explainable Pairwise Ranking from Implicit Feedback","display_name":"Debiased Explainable Pairwise Ranking from Implicit Feedback","publication_year":2021,"publication_date":"2021-09-13","ids":{"openalex":"https://openalex.org/W3187508330","doi":"https://doi.org/10.1145/3460231.3474274","mag":"3187508330"},"language":"en","primary_location":{"id":"doi:10.1145/3460231.3474274","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460231.3474274","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2107.14768","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Khalil Damak","orcid":null},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Khalil Damak","raw_affiliation_strings":["Department of Computer Science and Engineering University of Louisville, United States"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering University of Louisville, United States","institution_ids":["https://openalex.org/I142740786"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Sami Khenissi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210143137","display_name":"University of Louisville Hospital","ror":"https://ror.org/04sq8k219","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210143137"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sami Khenissi","raw_affiliation_strings":["University of Louisville, United States"],"affiliations":[{"raw_affiliation_string":"University of Louisville, United States","institution_ids":["https://openalex.org/I4210143137"]}]},{"author_position":"last","author":{"id":null,"display_name":"Olfa Nasraoui","orcid":null},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Olfa Nasraoui","raw_affiliation_strings":["Dept of Computer Engineering and Computer Science University of Louisville, United States"],"affiliations":[{"raw_affiliation_string":"Dept of Computer Engineering and Computer Science University of Louisville, United States","institution_ids":["https://openalex.org/I142740786"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I142740786"],"apc_list":null,"apc_paid":null,"fwci":4.2578,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.946179,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"321","last_page":"331"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9936000108718872,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9825000166893005,"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/ranking","display_name":"Ranking (information retrieval)","score":0.7470999956130981},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.6676999926567078},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6026999950408936},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5321999788284302},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5027999877929688},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.48510000109672546},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.4041000008583069},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.3912000060081482}],"concepts":[{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7470999956130981},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7046999931335449},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.6676999926567078},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6026999950408936},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5321999788284302},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5273000001907349},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5027999877929688},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.48510000109672546},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4334000051021576},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.4041000008583069},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3926999866962433},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.3912000060081482},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.35409998893737793},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.34310001134872437},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3296000063419342},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.28679999709129333},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.28119999170303345},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.2687000036239624},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3460231.3474274","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460231.3474274","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2107.14768","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2107.14768","pdf_url":"https://arxiv.org/pdf/2107.14768","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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2107.14768","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2107.14768","pdf_url":"https://arxiv.org/pdf/2107.14768","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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1886704267","https://openalex.org/W1992380306","https://openalex.org/W2023603028","https://openalex.org/W2042281163","https://openalex.org/W2046216022","https://openalex.org/W2077927809","https://openalex.org/W2101409192","https://openalex.org/W2124187902","https://openalex.org/W2126159342","https://openalex.org/W2134584261","https://openalex.org/W2144807535","https://openalex.org/W2152184085","https://openalex.org/W2219888463","https://openalex.org/W2340502990","https://openalex.org/W2523451931","https://openalex.org/W2605350416","https://openalex.org/W2624617553","https://openalex.org/W2739992143","https://openalex.org/W2741249238","https://openalex.org/W2746910012","https://openalex.org/W2749348810","https://openalex.org/W2892888989","https://openalex.org/W2912967843","https://openalex.org/W2945357717","https://openalex.org/W2953218817","https://openalex.org/W2962989965","https://openalex.org/W2963655167","https://openalex.org/W2987225481","https://openalex.org/W2998534896","https://openalex.org/W2998673651","https://openalex.org/W3011809564","https://openalex.org/W3012576969","https://openalex.org/W3035264853","https://openalex.org/W3035397484","https://openalex.org/W3035596828","https://openalex.org/W3088120614","https://openalex.org/W3105819862","https://openalex.org/W3184115662","https://openalex.org/W4251597219"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"work":[1],"in":[2,15,19,51,87],"recommender":[3,137],"systems":[4],"has":[5,43],"emphasized":[6],"the":[7,30,33,84,88,91,109,126,136,178,192,223],"importance":[8],"of":[9,32,67,225],"fairness,":[10],"with":[11,166],"a":[12,72,96,145,151,184,199],"particular":[13],"interest":[14],"bias":[16,106,119,175],"and":[17,90,99,150,180,207],"transparency,":[18],"addition":[20],"to":[21,47,58,94,104,108,186],"predictive":[22,52],"accuracy.":[23],"In":[24,139],"this":[25,140],"paper,":[26],"we":[27,63,142,170,212],"focus":[28],"on":[29,217],"state":[31],"art":[34],"pairwise":[35],"ranking":[36,200],"model,":[37],"Bayesian":[38,158],"Personalized":[39,159],"Ranking":[40,160],"(BPR),":[41],"which":[42],"previously":[44],"been":[45],"found":[46],"outperform":[48],"pointwise":[49],"models":[50],"accuracy,":[53],"while":[54],"also":[55],"being":[56,111,133],"able":[57],"handle":[59],"implicit":[60],"feedback.":[61],"Specifically,":[62],"address":[64],"two":[65],"limitations":[66],"BPR:":[68],"(1)":[69],"BPR":[70,101],"is":[71,102,198],"black":[73],"box":[74],"model":[75,155,201],"that":[76,162,202,221],"does":[77],"not":[78],"explain":[79],"its":[80],"outputs,":[81],"thus":[82],"limiting":[83],"user\u2019s":[85],"trust":[86],"recommendations,":[89],"analyst\u2019s":[92],"ability":[93],"scrutinize":[95],"model\u2019s":[97],"outputs;":[98],"(2)":[100],"vulnerable":[103],"exposure":[105,118,174],"due":[107],"data":[110],"Missing":[112],"Not":[113],"At":[114],"Random":[115],"(MNAR).":[116],"This":[117],"usually":[120],"translates":[121],"into":[122],"an":[123,188,214],"unfairness":[124],"against":[125],"least":[127],"popular":[128],"items":[129],"because":[130],"they":[131],"risk":[132],"under-exposed":[134],"by":[135],"system.":[138],"work,":[141],"first":[143],"propose":[144,187],"novel":[146],"explainable":[147,208],"loss":[148],"function":[149],"corresponding":[152],"Matrix":[153],"Factorization-based":[154],"called":[156],"Explainable":[157],"(EBPR)":[161],"generates":[163],"recommendations":[164],"along":[165],"item-based":[167],"explanations.":[168],"Then,":[169],"theoretically":[171],"quantify":[172],"additional":[173],"resulting":[176],"from":[177],"explainability,":[179],"use":[181],"it":[182],"as":[183],"basis":[185],"unbiased":[189],"estimator":[190],"for":[191],"ideal":[193],"EBPR":[194],"loss.":[195],"The":[196],"result":[197],"aptly":[203],"captures":[204],"both":[205],"debiased":[206],"user":[209],"preferences.":[210],"Finally,":[211],"perform":[213],"empirical":[215],"study":[216],"three":[218],"real-world":[219],"datasets":[220],"demonstrate":[222],"advantages":[224],"our":[226],"proposed":[227],"models.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2021-08-16T00:00:00"}
