{"id":"https://openalex.org/W1974318090","doi":"https://doi.org/10.1145/2792838.2800185","title":"Gaussian Ranking by Matrix Factorization","display_name":"Gaussian Ranking by Matrix Factorization","publication_year":2015,"publication_date":"2015-09-08","ids":{"openalex":"https://openalex.org/W1974318090","doi":"https://doi.org/10.1145/2792838.2800185","mag":"1974318090"},"language":"en","primary_location":{"id":"doi:10.1145/2792838.2800185","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2792838.2800185","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2800185&type=pdf","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":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://dl.acm.org/ft_gateway.cfm?id=2800185&type=pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070327072","display_name":"Harald Steck","orcid":"https://orcid.org/0009-0007-7448-8335"},"institutions":[{"id":"https://openalex.org/I869089601","display_name":"Netflix (United States)","ror":"https://ror.org/0197qw696","country_code":"US","type":"company","lineage":["https://openalex.org/I869089601"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Harald Steck","raw_affiliation_strings":["Netflix, Los Gatos, CA, USA"],"affiliations":[{"raw_affiliation_string":"Netflix, Los Gatos, CA, USA","institution_ids":["https://openalex.org/I869089601"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5070327072"],"corresponding_institution_ids":["https://openalex.org/I869089601"],"apc_list":null,"apc_paid":null,"fwci":14.3028,"has_fulltext":true,"cited_by_count":31,"citation_normalized_percentile":{"value":0.98629274,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"115","last_page":"122"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9934999942779541,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9926999807357788,"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/recommender-system","display_name":"Recommender system","score":0.8586987257003784},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.7997196912765503},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7532908916473389},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7261109352111816},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5908301472663879},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5115583539009094},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.4609566032886505},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4530493915081024},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.45102235674858093},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4324425458908081},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.42690879106521606},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.42295706272125244},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3409954905509949},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30841779708862305},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19108846783638}],"concepts":[{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8586987257003784},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.7997196912765503},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7532908916473389},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7261109352111816},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5908301472663879},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5115583539009094},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4609566032886505},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4530493915081024},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.45102235674858093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4324425458908081},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.42690879106521606},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.42295706272125244},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3409954905509949},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30841779708862305},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19108846783638},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2792838.2800185","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2792838.2800185","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2800185&type=pdf","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":{"id":"doi:10.1145/2792838.2800185","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2792838.2800185","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2800185&type=pdf","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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1974318090.pdf","grobid_xml":"https://content.openalex.org/works/W1974318090.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W21006490","https://openalex.org/W1503442267","https://openalex.org/W1554663460","https://openalex.org/W1912982817","https://openalex.org/W1968598835","https://openalex.org/W1992665562","https://openalex.org/W1994389483","https://openalex.org/W1999956270","https://openalex.org/W2006822005","https://openalex.org/W2071111773","https://openalex.org/W2095705004","https://openalex.org/W2101409192","https://openalex.org/W2102035799","https://openalex.org/W2113242816","https://openalex.org/W2119384858","https://openalex.org/W2124187902","https://openalex.org/W2137245235","https://openalex.org/W2140310134","https://openalex.org/W2150886314","https://openalex.org/W2616052791","https://openalex.org/W2745560456"],"related_works":["https://openalex.org/W2772628444","https://openalex.org/W1484355083","https://openalex.org/W4220714703","https://openalex.org/W2098758514","https://openalex.org/W2735929803","https://openalex.org/W3008845055","https://openalex.org/W2170391450","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2508671622"],"abstract_inverted_index":{"The":[0],"ranking":[1,39],"quality":[2],"at":[3],"the":[4,7,57,76,99,134,137,147,150],"top":[5],"of":[6,15,78,101,149],"list":[8],"is":[9,42,125,142],"crucial":[10],"in":[11,98,145],"many":[12],"real-world":[13],"applications":[14],"recommender":[16,58],"systems.":[17],"In":[18,105],"this":[19,73,123],"paper,":[20],"we":[21,50,85,107],"present":[22],"a":[23,45,55,68,83],"novel":[24],"framework":[25],"that":[26,65,122],"allows":[27],"for":[28,53,62],"pointwise":[29],"as":[30,32,96],"well":[31],"listwise":[33],"training":[34,46],"with":[35,127,130],"respect":[36,131],"to":[37,132],"various":[38],"metrics.":[40],"This":[41],"based":[43],"on":[44],"objective":[47],"function":[48],"where":[49],"assume":[51],"that,":[52],"given":[54],"user,":[56],"system":[59],"predicts":[60],"scores":[61],"all":[63],"items":[64],"follow":[66],"approximately":[67],"Gaussian":[69,115],"distribution.":[70],"We":[71],"motivate":[72],"assumption":[74],"from":[75,113],"properties":[77],"implicit":[79],"feedback":[80],"data.":[81],"As":[82],"model,":[84],"use":[86,108],"matrix":[87],"factorization":[88],"and":[89],"extend":[90],"it":[91,141],"by":[92],"non-linear":[93,109],"activation":[94,110],"functions,":[95],"customary":[97],"literature":[100],"artificial":[102],"neural":[103],"networks.":[104],"particular,":[106],"functions":[111],"derived":[112],"our":[114],"assumption.":[116],"Our":[117],"preliminary":[118],"experimental":[119],"results":[120],"show":[121],"approach":[124],"competitive":[126],"state-of-the-art":[128],"methods":[129],"optimizing":[133,146],"Area":[135],"under":[136],"ROC":[138],"curve,":[139],"while":[140],"particularly":[143],"effective":[144],"head":[148],"ranked":[151],"list.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}