{"id":"https://openalex.org/W2035953455","doi":"https://doi.org/10.1145/2792838.2800195","title":"Letting Users Choose Recommender Algorithms","display_name":"Letting Users Choose Recommender Algorithms","publication_year":2015,"publication_date":"2015-09-08","ids":{"openalex":"https://openalex.org/W2035953455","doi":"https://doi.org/10.1145/2792838.2800195","mag":"2035953455"},"language":"en","primary_location":{"id":"doi:10.1145/2792838.2800195","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2792838.2800195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"conference-paper","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/A5015092805","display_name":"Michael D. Ekstrand","orcid":"https://orcid.org/0000-0003-2467-0108"},"institutions":[{"id":"https://openalex.org/I13511017","display_name":"Texas State University","ror":"https://ror.org/05h9q1g27","country_code":"US","type":"education","lineage":["https://openalex.org/I13511017"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael D. Ekstrand","raw_affiliation_strings":["Texas State University, San Marcos, TX, USA","Texas State University-San Marcos, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas State University, San Marcos, TX, USA","institution_ids":["https://openalex.org/I13511017"]},{"raw_affiliation_string":"Texas State University-San Marcos, TX, USA","institution_ids":["https://openalex.org/I13511017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072877746","display_name":"Daniel Kluver","orcid":"https://orcid.org/0000-0002-2810-7243"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Kluver","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA",", University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":", University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029009966","display_name":"F. Maxwell Harper","orcid":"https://orcid.org/0000-0003-0552-5773"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"F. Maxwell Harper","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA",", University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":", University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037387341","display_name":"Joseph A. Konstan","orcid":"https://orcid.org/0000-0002-7788-2748"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joseph A. Konstan","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA",", University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":", University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":89,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"11","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"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":1.0,"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":0.9958000183105469,"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":0.9699000120162964,"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/recommender-system","display_name":"Recommender system","score":0.8854131698608398},{"id":"https://openalex.org/keywords/movielens","display_name":"MovieLens","score":0.8611874580383301},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8402656316757202},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.7184373736381531},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6636289358139038},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5292876362800598},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43855413794517517},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42604124546051025},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4140566289424896}],"concepts":[{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8854131698608398},{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.8611874580383301},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8402656316757202},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.7184373736381531},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6636289358139038},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5292876362800598},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43855413794517517},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42604124546051025},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4140566289424896},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2792838.2800195","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2792838.2800195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1131917643","display_name":null,"funder_award_id":"IIS 08-08692,10-17697","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W281665770","https://openalex.org/W615621364","https://openalex.org/W1547786939","https://openalex.org/W1751428553","https://openalex.org/W1764008395","https://openalex.org/W1966553486","https://openalex.org/W1968380849","https://openalex.org/W2007636657","https://openalex.org/W2008961301","https://openalex.org/W2025019706","https://openalex.org/W2042281163","https://openalex.org/W2043403353","https://openalex.org/W2049291619","https://openalex.org/W2050125880","https://openalex.org/W2058806077","https://openalex.org/W2099716451","https://openalex.org/W2102378894","https://openalex.org/W2108790711","https://openalex.org/W2109328649","https://openalex.org/W2110228583","https://openalex.org/W2125330369","https://openalex.org/W2136016921","https://openalex.org/W2138216384","https://openalex.org/W2140074939","https://openalex.org/W2147859400","https://openalex.org/W2155106456","https://openalex.org/W2155912844","https://openalex.org/W2161351857","https://openalex.org/W2476960546","https://openalex.org/W2546986214","https://openalex.org/W4285719527","https://openalex.org/W4299687421"],"related_works":["https://openalex.org/W2355698112","https://openalex.org/W2022984797","https://openalex.org/W4394818607","https://openalex.org/W2986679525","https://openalex.org/W2797500822","https://openalex.org/W4299358966","https://openalex.org/W2794458286","https://openalex.org/W4205822456","https://openalex.org/W2537367858","https://openalex.org/W3173811578"],"abstract_inverted_index":{"Recommender":[0],"systems":[1],"are":[2],"not":[3,239],"one-size-fits-all;":[4],"different":[5,11,21,37,226],"algorithms":[6,81,131,170,210,222],"and":[7,23,52,82,109,116,138,178],"data":[8,98],"sources":[9],"have":[10],"strengths,":[12],"making":[13],"them":[14],"a":[15,69,118,148,171,175,195,217],"better":[16],"or":[17],"worse":[18],"fit":[19],"for":[20,229],"users":[22,41,84,111,137,163,193,205,231],"use":[24,57],"cases.":[25],"As":[26],"one":[27],"way":[28],"of":[29,32,36,58,68,72,129,151,162,192,208,242],"taking":[30],"advantage":[31],"the":[33,42,46,66,73,87,127,130,157,166,230,233],"relative":[34],"merits":[35],"algorithms,":[38,115],"we":[39],"gave":[40],"ability":[43],"to":[44,85,91,106,121,142],"change":[45],"algorithm":[47,88,120,183],"providing":[48],"their":[49,93,140],"movie":[50,75],"recommendations":[51],"studied":[53],"how":[54,110],"they":[55,89,133,185,215],"make":[56],"this":[59,103],"power.":[60],"We":[61,95,123,145],"conducted":[62],"our":[63,152],"study":[64],"with":[65,102],"launch":[67],"new":[70,104],"version":[71],"MovieLens":[74],"recommender":[76,80,114,227],"that":[77,147,184],"supports":[78],"multiple":[79],"allows":[83],"choose":[86],"want":[90],"provide":[92],"recommendations.":[94],"examine":[96,139],"log":[97],"from":[99],"user":[100,143,153,243],"interactions":[101],"feature":[105],"under-stand":[107],"whether":[108],"switch":[112],"among":[113],"select":[117],"final":[119],"use.":[122],"also":[124],"look":[125],"at":[126],"properties":[128],"as":[132],"were":[134,238],"experienced":[135],"by":[136,201],"relationships":[141],"behavior.":[144],"found":[146],"substantial":[149],"portion":[150],"base":[154],"(25%)":[155],"used":[156,165],"recommender-switching":[158],"feature.":[159],"The":[160,189,221],"majority":[161],"who":[164],"control":[167],"only":[168],"switched":[169],"few":[172,176],"times,":[173],"trying":[174],"out":[177],"settling":[179],"down":[180],"on":[181],"an":[182],"would":[186],"leave":[187],"alone.":[188],"largest":[190],"number":[191],"prefer":[194],"matrix":[196],"factorization":[197],"algorithm,":[198],"followed":[199],"closely":[200],"item-item":[202],"collaborative":[203],"filtering;":[204],"selected":[206],"both":[207],"these":[209,236],"much":[211],"more":[212],"often":[213],"than":[214],"chose":[216],"non-personalized":[218],"mean":[219],"recommender.":[220],"did":[223],"produce":[224],"measurably":[225],"lists":[228],"in":[232],"study,":[234],"but":[235],"differences":[237],"directly":[240],"predictive":[241],"choice.":[244]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":15},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}