{"id":"https://openalex.org/W2017079111","doi":"https://doi.org/10.2753/jec1086-4415160104","title":"Collaborative Filtering with a User-Item Matrix Reduction Technique","display_name":"Collaborative Filtering with a User-Item Matrix Reduction Technique","publication_year":2011,"publication_date":"2011-10-01","ids":{"openalex":"https://openalex.org/W2017079111","doi":"https://doi.org/10.2753/jec1086-4415160104","mag":"2017079111"},"language":"en","primary_location":{"id":"doi:10.2753/jec1086-4415160104","is_oa":false,"landing_page_url":"https://doi.org/10.2753/jec1086-4415160104","pdf_url":null,"source":{"id":"https://openalex.org/S18436875","display_name":"International Journal of Electronic Commerce","issn_l":"1086-4415","issn":["1086-4415","1557-9301"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Electronic Commerce","raw_type":"journal-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/A5053656905","display_name":"Kyoung-jae Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I205490536","display_name":"Dongguk University","ror":"https://ror.org/057q6n778","country_code":"KR","type":"education","lineage":["https://openalex.org/I205490536"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyoung-jae Kim","raw_affiliation_strings":["a Dongguk University, Seoul, Korea","Dongguk University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"a Dongguk University, Seoul, Korea","institution_ids":["https://openalex.org/I205490536"]},{"raw_affiliation_string":"Dongguk University, Seoul, Korea","institution_ids":["https://openalex.org/I205490536"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010379074","display_name":"Hyunchul Ahn","orcid":"https://orcid.org/0000-0003-1867-6423"},"institutions":[{"id":"https://openalex.org/I110273157","display_name":"Kookmin University","ror":"https://ror.org/0049erg63","country_code":"KR","type":"education","lineage":["https://openalex.org/I110273157"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunchul Ahn","raw_affiliation_strings":["b Kookmin University, Korea","Kookmin University, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"b Kookmin University, Korea","institution_ids":["https://openalex.org/I110273157"]},{"raw_affiliation_string":"Kookmin University, Korea","institution_ids":["https://openalex.org/I110273157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3091,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.92218355,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"16","issue":"1","first_page":"107","last_page":"128"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9761000275611877,"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/T12384","display_name":"Customer churn and segmentation","score":0.9635000228881836,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.8545297384262085},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.8447250127792358},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7393794059753418},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.6332705020904541},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.6122286319732666},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4958411157131195},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4880601167678833},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.46804285049438477},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4575497508049011},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.43767422437667847},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3839924931526184},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36462002992630005},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3404539227485657},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28481391072273254},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14756235480308533},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.06826576590538025}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.8545297384262085},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.8447250127792358},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7393794059753418},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.6332705020904541},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.6122286319732666},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4958411157131195},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4880601167678833},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.46804285049438477},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4575497508049011},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.43767422437667847},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3839924931526184},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36462002992630005},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3404539227485657},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28481391072273254},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14756235480308533},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.06826576590538025},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","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":1,"locations":[{"id":"doi:10.2753/jec1086-4415160104","is_oa":false,"landing_page_url":"https://doi.org/10.2753/jec1086-4415160104","pdf_url":null,"source":{"id":"https://openalex.org/S18436875","display_name":"International Journal of Electronic Commerce","issn_l":"1086-4415","issn":["1086-4415","1557-9301"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Electronic Commerce","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W179787377","https://openalex.org/W206440355","https://openalex.org/W208128215","https://openalex.org/W1487629352","https://openalex.org/W1488971269","https://openalex.org/W1539738334","https://openalex.org/W1570159982","https://openalex.org/W1571061365","https://openalex.org/W1673941785","https://openalex.org/W1827130679","https://openalex.org/W1966745127","https://openalex.org/W1991616626","https://openalex.org/W1994410331","https://openalex.org/W1999047234","https://openalex.org/W1999211797","https://openalex.org/W2001467667","https://openalex.org/W2002458417","https://openalex.org/W2004338242","https://openalex.org/W2010581786","https://openalex.org/W2018573356","https://openalex.org/W2020181841","https://openalex.org/W2022575446","https://openalex.org/W2026091747","https://openalex.org/W2028036481","https://openalex.org/W2030848960","https://openalex.org/W2037851654","https://openalex.org/W2042100477","https://openalex.org/W2042281163","https://openalex.org/W2043403353","https://openalex.org/W2045418508","https://openalex.org/W2053811285","https://openalex.org/W2074144322","https://openalex.org/W2074249686","https://openalex.org/W2088203776","https://openalex.org/W2093799708","https://openalex.org/W2096581064","https://openalex.org/W2100719534","https://openalex.org/W2107686700","https://openalex.org/W2110325612","https://openalex.org/W2117354486","https://openalex.org/W2140190241","https://openalex.org/W2144636407","https://openalex.org/W2148949939","https://openalex.org/W2150329959","https://openalex.org/W2155939443","https://openalex.org/W2171213646","https://openalex.org/W2950332743","https://openalex.org/W3141271909","https://openalex.org/W6637259173"],"related_works":["https://openalex.org/W1484355083","https://openalex.org/W2772628444","https://openalex.org/W4220714703","https://openalex.org/W2735929803","https://openalex.org/W2170391450","https://openalex.org/W2098758514","https://openalex.org/W3008845055","https://openalex.org/W2041004656","https://openalex.org/W4376854386","https://openalex.org/W2508671622"],"abstract_inverted_index":{"Collaborative":[0],"filtering":[1],"(CF)":[2],"is":[3],"regarded":[4],"as":[5,20],"one":[6],"of":[7,22,32,49,91],"the":[8,30,47,96,112,118,127,132,143,150,157,166],"most":[9],"popular":[10],"recommendation":[11],"methods.":[12],"However,":[13],"CF":[14,40,62,168],"has":[15],"some":[16],"significant":[17],"weaknesses,":[18],"such":[19],"problems":[21],"sparsity":[23,128],"and":[24,37,63,80,102,162],"scalability.":[25],"Sparsity":[26],"causes":[27],"inaccuracy":[28],"in":[29,46,87],"formation":[31],"neighbors":[33],"with":[34,44],"similar":[35],"interests,":[36],"scalability":[38,151],"prevents":[39],"from":[41,104],"scaling":[42],"up":[43],"increases":[45],"number":[48],"users":[50,101],"and/or":[51],"items.":[52,139],"To":[53],"mitigate":[54],"these":[55],"problems,":[56,79],"this":[57,94],"study":[58],"proposes":[59],"a":[60,88,105],"hybrid":[61],"genetic":[64],"algorithm":[65],"(GA)":[66],"model.":[67,169],"GAs":[68],"are":[69],"widely":[70],"believed":[71],"to":[72,110,116,165],"be":[73],"effective":[74],"on":[75],"NP-complete":[76],"global":[77],"optimization":[78],"they":[81],"can":[82],"provide":[83],"good":[84],"suboptimal":[85],"solutions":[86],"reasonable":[89],"amount":[90],"time.":[92],"In":[93],"study,":[95],"GA":[97],"searches":[98],"for":[99,146],"relevant":[100],"items":[103],"user-item":[106,123],"matrix":[107,113,124],"not":[108],"only":[109],"condense":[111],"but":[114],"also":[115,141],"improve":[117],"prediction":[119],"accuracy.":[120],"The":[121],"reduced":[122],"may":[125],"reduce":[126],"problem":[129],"by":[130],"increasing":[131],"likelihood":[133],"that":[134,156],"different":[135],"customers":[136],"rate":[137],"common":[138],"It":[140],"shrinks":[142],"search":[144],"space":[145],"CF,":[147],"which":[148],"ameliorates":[149],"problem.":[152],"Experimental":[153],"results":[154],"show":[155],"proposed":[158],"model":[159],"improves":[160],"performance":[161],"speed":[163],"compared":[164],"typical":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}