{"id":"https://openalex.org/W2810479486","doi":"https://doi.org/10.1145/3167132.3167275","title":"Explicit or implicit feedback? engagement or satisfaction?","display_name":"Explicit or implicit feedback? engagement or satisfaction?","publication_year":2018,"publication_date":"2018-04-09","ids":{"openalex":"https://openalex.org/W2810479486","doi":"https://doi.org/10.1145/3167132.3167275","mag":"2810479486"},"language":"en","primary_location":{"id":"doi:10.1145/3167132.3167275","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3167132.3167275","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd Annual ACM Symposium on Applied Computing","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/A5086649532","display_name":"Qian Zhao","orcid":"https://orcid.org/0000-0002-3758-237X"},"institutions":[{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Qian Zhao","raw_affiliation_strings":["University of Minnesota"],"affiliations":[{"raw_affiliation_string":"University of Minnesota","institution_ids":["https://openalex.org/I2800403580"]}]},{"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/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"F. Maxwell Harper","raw_affiliation_strings":["University of Minnesota"],"affiliations":[{"raw_affiliation_string":"University of Minnesota","institution_ids":["https://openalex.org/I2800403580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056123613","display_name":"Gediminas Adomavi\u010dius","orcid":"https://orcid.org/0000-0001-5251-5098"},"institutions":[{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gediminas Adomavicius","raw_affiliation_strings":["University of Minnesota"],"affiliations":[{"raw_affiliation_string":"University of Minnesota","institution_ids":["https://openalex.org/I2800403580"]}]},{"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/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joseph A. Konstan","raw_affiliation_strings":["University of Minnesota"],"affiliations":[{"raw_affiliation_string":"University of Minnesota","institution_ids":["https://openalex.org/I2800403580"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5086649532"],"corresponding_institution_ids":["https://openalex.org/I2800403580"],"apc_list":null,"apc_paid":null,"fwci":3.5998,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.93055911,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1331","last_page":"1340"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9991000294685364,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9990000128746033,"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/T10603","display_name":"Smart Grid Energy Management","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.8855176568031311},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8123171329498291},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6747461557388306},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5921210646629333},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49926209449768066},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.44125327467918396},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.43185582756996155},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.36140769720077515}],"concepts":[{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8855176568031311},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8123171329498291},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6747461557388306},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5921210646629333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49926209449768066},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.44125327467918396},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.43185582756996155},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.36140769720077515},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3167132.3167275","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3167132.3167275","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd Annual ACM Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1436238478","display_name":null,"funder_award_id":"IIS-1319382","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W21207210","https://openalex.org/W1095970959","https://openalex.org/W1480376833","https://openalex.org/W1486317198","https://openalex.org/W1511558225","https://openalex.org/W1515851193","https://openalex.org/W1657011257","https://openalex.org/W1663973292","https://openalex.org/W1690919088","https://openalex.org/W2007528787","https://openalex.org/W2049670925","https://openalex.org/W2054141820","https://openalex.org/W2094286023","https://openalex.org/W2100379340","https://openalex.org/W2101409192","https://openalex.org/W2107726111","https://openalex.org/W2112420033","https://openalex.org/W2112856797","https://openalex.org/W2114538223","https://openalex.org/W2118075434","https://openalex.org/W2123830992","https://openalex.org/W2125330369","https://openalex.org/W2138108551","https://openalex.org/W2140310134","https://openalex.org/W2155195660","https://openalex.org/W2155912844","https://openalex.org/W2156455250","https://openalex.org/W2162111811","https://openalex.org/W2275802500","https://openalex.org/W2312609093","https://openalex.org/W2341535507","https://openalex.org/W2583674722","https://openalex.org/W2588833253","https://openalex.org/W2603931454","https://openalex.org/W2962802563","https://openalex.org/W4214717370","https://openalex.org/W4226280022","https://openalex.org/W4293585414","https://openalex.org/W6630221451","https://openalex.org/W6703949738"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W2056712470","https://openalex.org/W2963185427","https://openalex.org/W4401051025","https://openalex.org/W2065296176"],"abstract_inverted_index":{"Recommender":[0],"systems":[1,83],"algorithms":[2,25,57],"are":[3,167],"generally":[4],"evaluated":[5],"primarily":[6],"on":[7],"machine":[8,60],"learning":[9,61,70,187],"criteria":[10],"such":[11],"as":[12,140,142],"recommendation":[13,24],"accuracy":[14],"or":[15],"top-n":[16],"precision.":[17],"In":[18,40],"this":[19],"work,":[20],"we":[21,54],"evaluate":[22],"six":[23,56],"from":[26,64,125,182],"a":[27,41,52,89],"user-centric":[28],"perspective,":[29],"collecting":[30],"both":[31,177],"objective":[32,78],"user":[33,38,86,163,171],"activity":[34],"data":[35,129],"and":[36,162,179,195],"subjective":[37],"perceptions.":[39],"field":[42],"experiment":[43],"involving":[44],"1508":[45],"users":[46,98,183],"who":[47],"participated":[48],"for":[49,92,102],"at":[50],"least":[51],"month,":[53],"compare":[55],"built":[58],"using":[59],"techniques,":[62],"ranging":[63],"supervised":[65],"matrix":[66,112],"factorization,":[67],"contextual":[68],"bandit":[69],"to":[71,130],"Q":[72],"learning.":[73],"We":[74,173],"found":[75],"that":[76,147,175],"the":[77,110,118,135,143,191,199,203],"design":[79],"in":[80,146],"machine-learning-based":[81],"recommender":[82,90,122,137,145],"significantly":[84],"affects":[85],"experience.":[87],"Specifically,":[88],"optimizing":[91,101],"implicit":[93,131,180],"action":[94,160],"prediction":[95,105],"error":[96,106],"engages":[97],"more":[99],"than":[100],"explicit":[103,127,178],"rating":[104],"when":[107],"modeled":[108],"with":[109,170],"classical":[111],"factorization":[113],"algorithms,":[114],"which":[115,166],"empirically":[116],"explains":[117],"historical":[119],"transition":[120],"of":[121,193,198],"system":[123],"research":[124],"modeling":[126],"feedback":[128,132,181],"data.":[133],"However,":[134],"action-based":[136],"is":[138],"not":[139,150],"precise":[141],"rating-based":[144],"it":[148],"increases":[149],"only":[151],"positive":[152],"engagement":[153,194],"but":[154],"also":[155],"negative":[156,159],"engagement,":[157],"e.g.,":[158],"rate":[161],"browsing":[164,205],"effort":[165],"negatively":[168],"correlated":[169],"satisfaction.":[172],"show":[174],"blending":[176],"through":[184],"an":[185],"online":[186],"algorithm":[188],"can":[189],"gain":[190],"benefits":[192],"mitigate":[196],"one":[197],"possible":[200],"costs":[201],"(i.e.,":[202],"increased":[204],"effort).":[206]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}