{"id":"https://openalex.org/W3210297745","doi":"https://doi.org/10.1145/3459637.3482020","title":"ULTRA: An Unbiased Learning To Rank Algorithm Toolbox","display_name":"ULTRA: An Unbiased Learning To Rank Algorithm Toolbox","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3210297745","doi":"https://doi.org/10.1145/3459637.3482020","mag":"3210297745"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482020","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060764305","display_name":"Anh Tu Tran","orcid":"https://orcid.org/0000-0001-9131-4491"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anh Tran","raw_affiliation_strings":["University of Utah, Salt Lake City, UT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Utah, Salt Lake City, UT, USA","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027201139","display_name":"Tao Yang","orcid":"https://orcid.org/0000-0001-6265-6177"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tao Yang","raw_affiliation_strings":["University of Utah, Salt Lake City, UT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Utah, Salt Lake City, UT, USA","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089655391","display_name":"Qingyao Ai","orcid":"https://orcid.org/0000-0002-5030-709X"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qingyao Ai","raw_affiliation_strings":["University of Utah, Salt Lake City, UT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Utah, Salt Lake City, UT, USA","institution_ids":["https://openalex.org/I223532165"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I223532165"],"apc_list":null,"apc_paid":null,"fwci":2.5608,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.91378571,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4613","last_page":"4622"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9980000257492065,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9980000257492065,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9970999956130981,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/toolbox","display_name":"Toolbox","score":0.849177360534668},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8231039643287659},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.7862251400947571},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6612899899482727},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6553823351860046},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6376935839653015},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6225263476371765},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5939478874206543},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5263121128082275},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5257844924926758},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5244612693786621},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5038356184959412},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35012727975845337},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34127241373062134}],"concepts":[{"id":"https://openalex.org/C2777655017","wikidata":"https://www.wikidata.org/wiki/Q1501161","display_name":"Toolbox","level":2,"score":0.849177360534668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8231039643287659},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.7862251400947571},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6612899899482727},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6553823351860046},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6376935839653015},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6225263476371765},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5939478874206543},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5263121128082275},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5257844924926758},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5244612693786621},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5038356184959412},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35012727975845337},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34127241373062134},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3459637.3482020","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1973435495","https://openalex.org/W1974360117","https://openalex.org/W2003473029","https://openalex.org/W2009979684","https://openalex.org/W2014415866","https://openalex.org/W2047221353","https://openalex.org/W2090883204","https://openalex.org/W2096438175","https://openalex.org/W2108862644","https://openalex.org/W2115584760","https://openalex.org/W2120391124","https://openalex.org/W2143331230","https://openalex.org/W2149427297","https://openalex.org/W2152314154","https://openalex.org/W2279385734","https://openalex.org/W2340526403","https://openalex.org/W2507134384","https://openalex.org/W2769473018","https://openalex.org/W2771647914","https://openalex.org/W2796727080","https://openalex.org/W2797400361","https://openalex.org/W2798634418","https://openalex.org/W2799226155","https://openalex.org/W2890291106","https://openalex.org/W2891508226","https://openalex.org/W2897785891","https://openalex.org/W2905569957","https://openalex.org/W2911802745","https://openalex.org/W2912255075","https://openalex.org/W2955421345","https://openalex.org/W2965893800","https://openalex.org/W2975938167","https://openalex.org/W2985671795","https://openalex.org/W2997842202","https://openalex.org/W3035590471","https://openalex.org/W3101997094","https://openalex.org/W3102540985","https://openalex.org/W3103733168","https://openalex.org/W3105712174","https://openalex.org/W3105997200","https://openalex.org/W3130740428"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W3160516639","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W4390446658","https://openalex.org/W2971071571","https://openalex.org/W2798835721","https://openalex.org/W2922169395","https://openalex.org/W2387658907"],"abstract_inverted_index":{"Learning":[0],"to":[1,21,25,59,105,119,133,136,183,196,249],"rank":[2,26,60,197],"system":[3],"has":[4,46],"become":[5,47],"an":[6,48,244],"important":[7,49,245],"aspect":[8],"of":[9,174,208,221],"our":[10],"daily":[11],"life.":[12],"However,":[13],"the":[14,121,134,205,212,217,222,228,236,266],"implicit":[15],"user":[16,34,87],"feedback":[17,45],"that":[18,68,78,178,235],"is":[19,28,150,239,243],"used":[20,181],"train":[22],"many":[23,95],"learning":[24,58,195],"models":[27,177],"usually":[29],"noisy":[30],"and":[31,76,107,138,154,190,193,219,233],"suffers":[32],"from":[33,97],"bias":[35],"(i.e.,":[36],"position":[37],"bias).":[38],"Thus,":[39],"obtaining":[40],"unbiased":[41,57,83],"model":[42,188],"using":[43],"biased":[44],"research":[50],"field":[51,135],"for":[52,117,124,128,164,247],"IR.":[53],"Existing":[54],"studies":[55],"on":[56,226,252],"(ULTR)":[61],"can":[62,114,179],"be":[63,115,180],"generalized":[64],"into":[65],"two":[66],"families-algorithms":[67],"attain":[69],"unbiasness":[70,80],"with":[71,85,168,255,265],"logged":[72],"data,":[73],"offline":[74],"learning,":[75],"algorithms":[77,96,167,213,229,254,264],"achieve":[79],"by":[81,231],"estimating":[82],"parameters":[84],"real-time":[86],"interactions,":[88],"namely":[89],"online":[90],"learning.":[91],"While":[92],"there":[93,100],"exist":[94],"both":[98],"families,":[99],"lacks":[101],"a":[102,111,151,172],"unified":[103],"way":[104],"compare":[106],"benchmark":[108],"them.":[109],"As":[110],"result,":[112],"it":[113],"challenging":[116],"researchers":[118,248],"choose":[120],"right":[122],"technique":[123],"their":[125,262],"problems":[126],"or":[127],"people":[129],"who":[130],"are":[131],"new":[132],"learn":[137],"understand":[139],"existing":[140],"algorithms.":[141],"To":[142],"solve":[143],"this":[144,201],"problem,":[145],"we":[146,203],"introduced":[147],"ULTRA,":[148,215],"which":[149],"flexible,":[152],"extensible,":[153],"easily":[155],"configure":[156],"ULTR":[157,166,253],"toolbox.":[158,223],"Its":[159],"key":[160],"features":[161],"include":[162],"support":[163],"multiple":[165],"configurable":[169],"hyper":[170],"parameters,":[171],"variety":[173],"built-in":[175],"click":[176],"separately":[182],"simulate":[184],"clicks,":[185],"different":[186,256],"ranking":[187],"architectures":[189],"evaluation":[191],"metrics,":[192],"simple":[194],"pipeline":[198,220],"creation.":[199],"In":[200],"paper,":[202],"discuss":[204],"general":[206],"framework":[207],"ULTR,":[209],"briefly":[210],"describe":[211],"in":[214],"detail":[216],"structure,":[218],"We":[224],"experimented":[225],"all":[227],"supported":[230,267],"ULTRA":[232],"showed":[234],"toolbox":[237,242],"performance":[238],"reasonable.":[240],"Our":[241],"resource":[246],"conduct":[250],"experiments":[251],"configurations":[257],"as":[258,260],"well":[259],"testing":[261],"own":[263],"features.":[268]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}