{"id":"https://openalex.org/W1967921672","doi":"https://doi.org/10.1145/1143844.1143876","title":"Collaborative prediction using ensembles of Maximum Margin Matrix Factorizations","display_name":"Collaborative prediction using ensembles of Maximum Margin Matrix Factorizations","publication_year":2006,"publication_date":"2006-01-01","ids":{"openalex":"https://openalex.org/W1967921672","doi":"https://doi.org/10.1145/1143844.1143876","mag":"1967921672"},"language":"en","primary_location":{"id":"doi:10.1145/1143844.1143876","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1143844.1143876","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd international conference on Machine learning  - ICML '06","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/A5108368276","display_name":"Dennis DeCoste","orcid":null},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]},{"id":"https://openalex.org/I1325784139","display_name":"Yahoo (United Kingdom)","ror":"https://ror.org/038p3gq39","country_code":"GB","type":"company","lineage":["https://openalex.org/I1325784139","https://openalex.org/I4210134091"]}],"countries":["GB","US"],"is_corresponding":true,"raw_author_name":"Dennis DeCoste","raw_affiliation_strings":["Yahoo! Research, Burbank, CA","Yahoo! Research, Burbank, CA#TAB#"],"affiliations":[{"raw_affiliation_string":"Yahoo! Research, Burbank, CA","institution_ids":["https://openalex.org/I4210134091"]},{"raw_affiliation_string":"Yahoo! Research, Burbank, CA#TAB#","institution_ids":["https://openalex.org/I1325784139"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5108368276"],"corresponding_institution_ids":["https://openalex.org/I1325784139","https://openalex.org/I4210134091"],"apc_list":null,"apc_paid":null,"fwci":2.3157,"has_fulltext":false,"cited_by_count":99,"citation_normalized_percentile":{"value":0.87127205,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"249","last_page":"256"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10269","display_name":"Epigenetics and DNA Methylation","score":0.9344000220298767,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10269","display_name":"Epigenetics and DNA Methylation","score":0.9344000220298767,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9330999851226807,"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"}},{"id":"https://openalex.org/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9200999736785889,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.7677508592605591},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.677304744720459},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5516687631607056},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5122455954551697},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.4568203091621399},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4459795653820038},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43722736835479736},{"id":"https://openalex.org/keywords/movielens","display_name":"MovieLens","score":0.4272949695587158},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3406936228275299},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.307489812374115},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.14301547408103943},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.12526899576187134},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08631807565689087},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.08238735795021057}],"concepts":[{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.7677508592605591},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.677304744720459},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5516687631607056},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5122455954551697},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4568203091621399},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4459795653820038},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43722736835479736},{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.4272949695587158},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3406936228275299},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.307489812374115},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.14301547408103943},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.12526899576187134},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08631807565689087},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.08238735795021057},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1143844.1143876","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1143844.1143876","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd international conference on Machine learning  - ICML '06","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.78.5849","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.78.5849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://imls.engr.oregonstate.edu/www/htdocs/proceedings/icml2006/032_Collaborative_Predic.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.5199999809265137,"display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1510348757","https://openalex.org/W1532852017","https://openalex.org/W1540358749","https://openalex.org/W1556849888","https://openalex.org/W1673941785","https://openalex.org/W1902027874","https://openalex.org/W1976618413","https://openalex.org/W2049455633","https://openalex.org/W2109720450","https://openalex.org/W2113858518","https://openalex.org/W2118079529","https://openalex.org/W2122090912","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2125326641","https://openalex.org/W1504001548","https://openalex.org/W4288429585","https://openalex.org/W2054286941","https://openalex.org/W2142984176","https://openalex.org/W2554601002","https://openalex.org/W210173153","https://openalex.org/W2097588749","https://openalex.org/W2011407342","https://openalex.org/W125384550"],"abstract_inverted_index":{"Fast":[0],"gradient-based":[1],"methods":[2,26],"for":[3],"Maximum":[4],"Margin":[5],"Matrix":[6],"Factorization":[7],"(MMMF)":[8],"were":[9],"recently":[10],"shown":[11],"to":[12,41,64,109],"have":[13],"great":[14],"promise":[15],"(Rennie":[16],"&":[17],"Srebro,":[18],"2005),":[19],"including":[20],"significantly":[21,76],"outperforming":[22],"the":[23,44],"previous":[24],"state-of-the-art":[25],"on":[27],"some":[28],"standard":[29],"collaborative":[30],"prediction":[31],"benchmarks":[32],"(including":[33],"MovieLens).":[34],"In":[35,87],"this":[36],"paper,":[37],"we":[38,89],"investigate":[39],"ways":[40,63],"further":[42],"improve":[43],"performance":[45],"of":[46,61,93],"MMMF,":[47],"by":[48],"casting":[49],"it":[50],"within":[51],"an":[52],"ensemble":[53],"approach.":[54],"We":[55,68],"explore":[56],"and":[57],"evaluate":[58],"a":[59,79,110],"variety":[60],"alternative":[62],"define":[65],"such":[66],"ensembles.":[67],"show":[69],"that":[70,91],"our":[71],"resulting":[72],"ensembles":[73,92],"can":[74,98],"perform":[75],"better":[77,102],"than":[78],"single":[80,111],"MMMF":[81,96,112],"model,":[82],"along":[83],"multiple":[84],"evaluation":[85],"metrics.":[86],"fact,":[88],"find":[90],"partially":[94],"trained":[95],"models":[97],"sometimes":[99],"even":[100],"give":[101],"predictions":[103],"in":[104],"total":[105],"training":[106],"time":[107],"comparable":[108],"model.":[113]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":13},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":9}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
