{"id":"https://openalex.org/W4281633849","doi":"https://doi.org/10.26599/bdma.2021.9020032","title":"Optimal Dependence of Performance and Efficiency of Collaborative Filtering on Random Stratified Subsampling","display_name":"Optimal Dependence of Performance and Efficiency of Collaborative Filtering on Random Stratified Subsampling","publication_year":2022,"publication_date":"2022-06-09","ids":{"openalex":"https://openalex.org/W4281633849","doi":"https://doi.org/10.26599/bdma.2021.9020032"},"language":"en","primary_location":{"id":"doi:10.26599/bdma.2021.9020032","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2021.9020032","pdf_url":"https://ieeexplore.ieee.org/ielx7/8254253/9793354/09793360.pdf","source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ieeexplore.ieee.org/ielx7/8254253/9793354/09793360.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090427382","display_name":"Samin Poudel","orcid":"https://orcid.org/0000-0002-4431-2124"},"institutions":[{"id":"https://openalex.org/I35777872","display_name":"North Carolina Agricultural and Technical State University","ror":"https://ror.org/02aze4h65","country_code":"US","type":"education","lineage":["https://openalex.org/I35777872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samin Poudel","raw_affiliation_strings":["North Carolina A&#x0026;T State University,Department of Computational Data Science and Engineering,Greensboro,NC,USA,27401"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Carolina A&#x0026;T State University,Department of Computational Data Science and Engineering,Greensboro,NC,USA,27401","institution_ids":["https://openalex.org/I35777872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091815113","display_name":"Marwan Bikdash","orcid":"https://orcid.org/0000-0002-7333-8227"},"institutions":[{"id":"https://openalex.org/I35777872","display_name":"North Carolina Agricultural and Technical State University","ror":"https://ror.org/02aze4h65","country_code":"US","type":"education","lineage":["https://openalex.org/I35777872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marwan Bikdash","raw_affiliation_strings":["North Carolina A&#x0026;T State University,Department of Computational Data Science and Engineering,Greensboro,NC,USA,27401"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Carolina A&#x0026;T State University,Department of Computational Data Science and Engineering,Greensboro,NC,USA,27401","institution_ids":["https://openalex.org/I35777872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.0546,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.96410755,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"5","issue":"3","first_page":"192","last_page":"205"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9988999962806702,"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":0.9988999962806702,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.987500011920929,"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"}},{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.972599983215332,"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/fraction","display_name":"Fraction (chemistry)","score":0.6872556209564209},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6319321990013123},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5403994917869568},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.536088764667511},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.5262717008590698},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.495608925819397},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.48963862657546997},{"id":"https://openalex.org/keywords/movielens","display_name":"MovieLens","score":0.4289293885231018},{"id":"https://openalex.org/keywords/variance-reduction","display_name":"Variance reduction","score":0.42019224166870117},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4102160334587097},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3684318959712982},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3343117833137512},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32087138295173645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29538553953170776},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.238005131483078},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.13439178466796875},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.1286628544330597}],"concepts":[{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.6872556209564209},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6319321990013123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5403994917869568},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.536088764667511},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.5262717008590698},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.495608925819397},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.48963862657546997},{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.4289293885231018},{"id":"https://openalex.org/C62644790","wikidata":"https://www.wikidata.org/wiki/Q3454689","display_name":"Variance reduction","level":3,"score":0.42019224166870117},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4102160334587097},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3684318959712982},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3343117833137512},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32087138295173645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29538553953170776},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.238005131483078},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.13439178466796875},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.1286628544330597},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.26599/bdma.2021.9020032","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2021.9020032","pdf_url":"https://ieeexplore.ieee.org/ielx7/8254253/9793354/09793360.pdf","source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:bdb6b5fe54ab481eabd106dec2fc3105","is_oa":true,"landing_page_url":"https://doaj.org/article/bdb6b5fe54ab481eabd106dec2fc3105","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data Mining and Analytics, Vol 5, Iss 3, Pp 192-205 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.26599/bdma.2021.9020032","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2021.9020032","pdf_url":"https://ieeexplore.ieee.org/ielx7/8254253/9793354/09793360.pdf","source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4281633849.pdf","grobid_xml":"https://content.openalex.org/works/W4281633849.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1139185857","https://openalex.org/W1622081585","https://openalex.org/W2019313057","https://openalex.org/W2024095636","https://openalex.org/W2054141820","https://openalex.org/W2081332171","https://openalex.org/W2099113722","https://openalex.org/W2100235918","https://openalex.org/W2102148524","https://openalex.org/W2112596352","https://openalex.org/W2119523409","https://openalex.org/W2136944193","https://openalex.org/W2152208379","https://openalex.org/W2156701939","https://openalex.org/W2189280035","https://openalex.org/W2408207485","https://openalex.org/W2592414564","https://openalex.org/W2596629674","https://openalex.org/W2765564115","https://openalex.org/W2800023445","https://openalex.org/W2898151875","https://openalex.org/W2940239237","https://openalex.org/W2950332743","https://openalex.org/W2971196067","https://openalex.org/W3003257820","https://openalex.org/W3008901930","https://openalex.org/W3030286867","https://openalex.org/W3034216953","https://openalex.org/W3036259501","https://openalex.org/W3047010778","https://openalex.org/W4248672808","https://openalex.org/W6676522543","https://openalex.org/W6686981710","https://openalex.org/W6734416042","https://openalex.org/W6745117755","https://openalex.org/W6842875748","https://openalex.org/W6917172014"],"related_works":["https://openalex.org/W2797500822","https://openalex.org/W2355698112","https://openalex.org/W2022984797","https://openalex.org/W2986679525","https://openalex.org/W4205822456","https://openalex.org/W4299358966","https://openalex.org/W2537367858","https://openalex.org/W2981634480","https://openalex.org/W2188396403","https://openalex.org/W2368078825"],"abstract_inverted_index":{"Dropping":[0],"fractions":[1],"of":[2,12,19,28,67,73,92,105,113,156,198,231,247],"users":[3],"or":[4,40],"items":[5],"judiciously":[6],"can":[7,172],"reduce":[8],"the":[9,23,64,80,93,99,196,201,215,221,234,244],"computational":[10],"cost":[11],"Collaborative":[13],"Filtering":[14],"(CF)":[15],"algorithms.":[16],"The":[17,152,188],"effect":[18],"this":[20,49],"subsampling":[21,43,84,199,236],"on":[22,110],"computing":[24],"time":[25],"and":[26,34,71,79,98,107,129,138,146,178,205,233],"accuracy":[27],"CF":[29,116,158],"is":[30,85,218],"not":[31,46],"fully":[32],"understood,":[33],"clear":[35],"guidelines":[36],"for":[37,148,164,228],"selecting":[38],"optimal":[39,216,222,235,239],"even":[41],"appropriate":[42],"levels":[44,197],"are":[45,77,142,191,241],"available.":[47],"In":[48],"paper,":[50],"we":[51,88],"present":[52],"a":[53,139,157],"Density-based":[54],"Random":[55],"Stratified":[56],"Subsampling":[57],"using":[58],"Clustering":[59],"(DRSC)":[60],"algorithm":[61],"in":[62,144,213],"which":[63,214],"desired":[65],"Fraction":[66,72],"Users":[68],"Dropped":[69,75],"(FUD)":[70],"Items":[74],"(FID)":[76],"specified,":[78],"overall":[81],"density":[82],"during":[83],"maintained.":[86],"Subsequently,":[87],"develop":[89],"simple":[90,208],"models":[91,190],"Training":[94,223],"Time":[95,224],"Improvement":[96],"(TTI)":[97],"Accuracy":[100],"Loss":[101],"(AL)":[102],"as":[103,118],"functions":[104],"FUD":[106,147,177],"FID,":[108],"based":[109],"extensive":[111],"simulations":[112,168],"seven":[114,150],"standard":[115],"algorithms":[117],"applied":[119],"to":[120,161,194,220,243],"various":[121],"primary":[122],"matrices":[123],"from":[124],"MovieLens,":[125],"Yahoo":[126],"Music":[127],"Rating,":[128],"Amazon":[130],"Automotive":[131],"data.":[132],"Simulations":[133],"show":[134],"that":[135,170],"both":[136],"TTI":[137,153,171,204],"scaled":[140],"AL":[141,182,217],"bi-linear":[143],"FID":[145,179],"all":[149,165],"methods.":[151],"linear":[154],"regression":[155],"method":[159],"appears":[160],"be":[162,173],"same":[163],"datasets.":[166],"Extensive":[167],"illustrate":[169],"estimated":[174],"reliably":[175],"with":[176],"only,":[180],"but":[181],"requires":[183],"considering":[184],"additional":[185],"dataset":[186],"characteristics.":[187],"derived":[189],"then":[192],"used":[193],"optimize":[195],"addressing":[200],"tradeoff":[202],"between":[203],"AL.":[206],"A":[207],"sub-optimal":[209],"approximation":[210],"was":[211],"found,":[212],"proportional":[219,242],"Reduction":[225],"Factor":[226],"(TTRF)":[227],"higher":[229],"values":[230],"TTRF,":[232],"levels,":[237],"like":[238],"FID/(1\u2013FID),":[240],"square":[245],"root":[246],"TTRF.":[248]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
