{"id":"https://openalex.org/W2741249253","doi":"https://doi.org/10.24963/ijcai.2017/223","title":"Privileged Matrix Factorization for Collaborative Filtering","display_name":"Privileged Matrix Factorization for Collaborative Filtering","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2741249253","doi":"https://doi.org/10.24963/ijcai.2017/223","mag":"2741249253"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2017/223","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/223","pdf_url":"https://www.ijcai.org/proceedings/2017/0223.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2017/0223.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002080576","display_name":"Yali Du","orcid":"https://orcid.org/0000-0001-5683-2621"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yali Du","raw_affiliation_strings":["Center for Artificial Intelligence, FEIT, University of Technology Sydney"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Artificial Intelligence, FEIT, University of Technology Sydney","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001529504","display_name":"Chang Xu","orcid":"https://orcid.org/0000-0002-4756-0609"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]},{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Chang Xu","raw_affiliation_strings":["UBTech Sydney AI Institute, School of IT, FEIT, The University of Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UBTech Sydney AI Institute, School of IT, FEIT, The University of Sydney, Australia","institution_ids":["https://openalex.org/I114017466","https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074103823","display_name":"Dacheng Tao","orcid":"https://orcid.org/0000-0001-7225-5449"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]},{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Dacheng Tao","raw_affiliation_strings":["UBTech Sydney AI Institute and SIT, FEIT, The University of Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UBTech Sydney AI Institute and SIT, FEIT, The University of Sydney, Australia","institution_ids":["https://openalex.org/I114017466","https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.0512,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.94704255,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1610","last_page":"1616"},"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/T10609","display_name":"Digital Marketing and Social Media","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.7970963716506958},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7860854864120483},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6931860446929932},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6414802670478821},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.5555338859558105},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5127952694892883},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.48892107605934143},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.48324450850486755},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4483385384082794},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43362730741500854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4291277527809143},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.32407456636428833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.31842201948165894},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.06875842809677124}],"concepts":[{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.7970963716506958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7860854864120483},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6931860446929932},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6414802670478821},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.5555338859558105},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5127952694892883},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.48892107605934143},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.48324450850486755},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4483385384082794},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43362730741500854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4291277527809143},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32407456636428833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31842201948165894},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.06875842809677124},{"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2017/223","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/223","pdf_url":"https://www.ijcai.org/proceedings/2017/0223.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/126369","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/126369","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2017/223","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/223","pdf_url":"https://www.ijcai.org/proceedings/2017/0223.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2741249253.pdf","grobid_xml":"https://content.openalex.org/works/W2741249253.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W89654658","https://openalex.org/W338404229","https://openalex.org/W1530276735","https://openalex.org/W1551942318","https://openalex.org/W1563739387","https://openalex.org/W1614298861","https://openalex.org/W1853953842","https://openalex.org/W1976618413","https://openalex.org/W1990608327","https://openalex.org/W2008886893","https://openalex.org/W2018049374","https://openalex.org/W2028594831","https://openalex.org/W2042281163","https://openalex.org/W2050096199","https://openalex.org/W2054553473","https://openalex.org/W2061873838","https://openalex.org/W2067562626","https://openalex.org/W2102112650","https://openalex.org/W2108753466","https://openalex.org/W2131744502","https://openalex.org/W2133266261","https://openalex.org/W2136738361","https://openalex.org/W2137245235","https://openalex.org/W2153579005","https://openalex.org/W2156701939","https://openalex.org/W2173379916","https://openalex.org/W2183517875","https://openalex.org/W2359108789","https://openalex.org/W2397024933","https://openalex.org/W2397638129","https://openalex.org/W2399812666","https://openalex.org/W2408400968","https://openalex.org/W2577436636","https://openalex.org/W2949547296","https://openalex.org/W2950577311","https://openalex.org/W3102701984","https://openalex.org/W4294170691","https://openalex.org/W4300546991"],"related_works":["https://openalex.org/W2772628444","https://openalex.org/W2735929803","https://openalex.org/W4220714703","https://openalex.org/W1484355083","https://openalex.org/W3008845055","https://openalex.org/W2098758514","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2508671622","https://openalex.org/W2556532874"],"abstract_inverted_index":{"Collaborative":[0],"filtering":[1],"plays":[2],"a":[3,25,88,132],"crucial":[4],"role":[5],"in":[6,10,33,43,72,114,159],"reducing":[7],"excessive":[8],"information":[9,157],"online":[11],"consuming":[12],"by":[13,147],"suggesting":[14],"products":[15],"to":[16],"customers":[17],"that":[18,24,68,84,111],"fulfil":[19],"their":[20],"potential":[21],"interests.":[22],"Observing":[23],"user's":[26],"review":[27,41,86,101,125,161],"comments":[28,162],"on":[29,173],"purchases":[30],"are":[31,70],"often":[32],"companion":[34],"with":[35],"ratings,":[36],"recent":[37],"works":[38,66],"exploit":[39],"the":[40,74,98,106,115,128,137,156,160,164,178,181],"texts":[42,126],"representing":[44],"user":[45,78,91,119,168],"or":[46,79],"item":[47,80,93,121,170],"factors":[48,81],"and":[49,92,120,142,150,169],"have":[50],"achieved":[51],"prominent":[52],"performance.":[53],"Although":[54],"effectiveness":[55,179],"of":[56,64,76,90,100,117,166,180],"reviews":[57,69,113],"has":[58],"been":[59],"verified,":[60],"one":[61],"major":[62],"defect":[63],"existing":[65],"is":[67],"used":[71],"justifying":[73],"learning":[75,116,165],"either":[77],"without":[82],"noticing":[83],"each":[85],"associates":[87],"pair":[89],"concurrently.":[94],"To":[95],"better":[96],"explore":[97],"value":[99],"comments,":[102],"this":[103],"paper":[104],"presents":[105],"privileged":[107,129,134],"matrix":[108],"factorization":[109],"method":[110,154],"utilize":[112],"both":[118,167],"factors.":[122,171],"By":[123],"mapping":[124],"into":[127],"feature":[130],"space,":[131],"learned":[133],"function":[135],"compensates":[136],"discrepancies":[138,149],"between":[139],"predicted":[140],"ratings":[141],"groundtruth":[143],"values":[144],"rating-wisely.":[145],"Thus":[146],"minimizing":[148],"prediction":[151],"errors,":[152],"our":[153],"harnesses":[155],"present":[158],"for":[163],"Experiments":[172],"five":[174],"real":[175],"datasets":[176],"testify":[177],"proposed":[182],"method.":[183]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}