{"id":"https://openalex.org/W2911307904","doi":"https://doi.org/10.1080/08839514.2019.1577019","title":"Proposed RCFS-CARS Framework with Noise Detection and Correction","display_name":"Proposed RCFS-CARS Framework with Noise Detection and Correction","publication_year":2019,"publication_date":"2019-02-14","ids":{"openalex":"https://openalex.org/W2911307904","doi":"https://doi.org/10.1080/08839514.2019.1577019","mag":"2911307904"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2019.1577019","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2019.1577019","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"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":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5087479315","display_name":"Veer Sain Dixit","orcid":"https://orcid.org/0000-0003-1092-8657"},"institutions":[{"id":"https://openalex.org/I110166357","display_name":"University of Delhi","ror":"https://ror.org/04gzb2213","country_code":"IN","type":"education","lineage":["https://openalex.org/I110166357"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Veer Sain Dixit","raw_affiliation_strings":["Department of Computer Science, ARSD College, University of Delhi, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, ARSD College, University of Delhi, New Delhi, India","institution_ids":["https://openalex.org/I110166357"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102168066","display_name":"Parul Jain","orcid":null},"institutions":[{"id":"https://openalex.org/I110166357","display_name":"University of Delhi","ror":"https://ror.org/04gzb2213","country_code":"IN","type":"education","lineage":["https://openalex.org/I110166357"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Parul Jain","raw_affiliation_strings":["Department of Computer Science, ARSD College, University of Delhi, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, ARSD College, University of Delhi, New Delhi, India","institution_ids":["https://openalex.org/I110166357"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009625243","display_name":"Shalini Gupta","orcid":"https://orcid.org/0000-0002-4270-1222"},"institutions":[{"id":"https://openalex.org/I110166357","display_name":"University of Delhi","ror":"https://ror.org/04gzb2213","country_code":"IN","type":"education","lineage":["https://openalex.org/I110166357"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shalini Gupta","raw_affiliation_strings":["Department of Computer Science, ARSD College, University of Delhi, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, ARSD College, University of Delhi, New Delhi, India","institution_ids":["https://openalex.org/I110166357"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102168066"],"corresponding_institution_ids":["https://openalex.org/I110166357"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":0.3525,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65530303,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"33","issue":"4","first_page":"361","last_page":"377"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T11106","display_name":"Data Management and Algorithms","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.9178833961486816},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.8057394027709961},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.77144455909729},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.7070097327232361},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6799140572547913},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6624255180358887},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.523149847984314},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5153564810752869},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46571019291877747},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4093686044216156},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.36071574687957764},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3313519358634949},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.11020123958587646},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07249271869659424}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9178833961486816},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8057394027709961},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.77144455909729},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.7070097327232361},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6799140572547913},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6624255180358887},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.523149847984314},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5153564810752869},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46571019291877747},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4093686044216156},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.36071574687957764},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3313519358634949},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.11020123958587646},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07249271869659424},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2019.1577019","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2019.1577019","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"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":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8d9830b5ff304f029434659b07208d83","is_oa":false,"landing_page_url":"https://doaj.org/article/8d9830b5ff304f029434659b07208d83","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 33, Iss 4, Pp 361-377 (2019)","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W56073274","https://openalex.org/W151997209","https://openalex.org/W1560147776","https://openalex.org/W1576240472","https://openalex.org/W1586317846","https://openalex.org/W1978609982","https://openalex.org/W1996336859","https://openalex.org/W2002469552","https://openalex.org/W2006249313","https://openalex.org/W2010216744","https://openalex.org/W2034040856","https://openalex.org/W2047870744","https://openalex.org/W2053585176","https://openalex.org/W2070689335","https://openalex.org/W2082723490","https://openalex.org/W2083153244","https://openalex.org/W2148943147","https://openalex.org/W2291808414","https://openalex.org/W2400574415","https://openalex.org/W2404905139","https://openalex.org/W2408339918","https://openalex.org/W2573691746"],"related_works":["https://openalex.org/W2968745142","https://openalex.org/W2809363009","https://openalex.org/W2369936857","https://openalex.org/W2348159088","https://openalex.org/W2045871438","https://openalex.org/W2499363748","https://openalex.org/W2350747448","https://openalex.org/W2368095327","https://openalex.org/W2122731942","https://openalex.org/W2402445420"],"abstract_inverted_index":{"Context-Aware":[0],"Recommender":[1],"Systems":[2],"generate":[3],"more":[4],"relevant":[5],"recommendations":[6],"by":[7],"adapting":[8],"them":[9,122],"to":[10,42,59,68,98,112,123],"the":[11,20,26,76,105,114,118,125,136],"specific":[12],"contextual":[13,37,70],"situation":[14],"and":[15,45,78,120,139,148],"have":[16],"become":[17],"one":[18],"of":[19,50,61,80,104],"most":[21],"active":[22],"research":[23],"areas":[24],"in":[25,72,117,142,150],"recommender":[27,47],"systems.":[28,48],"However,":[29],"there":[30],"remains":[31],"a":[32,85,110],"key":[33],"issue":[34],"as":[35],"how":[36],"information":[38],"can":[39],"be":[40,99],"used":[41],"create":[43],"intelligent":[44],"useful":[46],"Use":[49],"too":[51],"many":[52],"context":[53,65],"variables":[54,66],"increases":[55],"dimensionality":[56],"that":[57,88,135],"leads":[58],"loss":[60],"accuracy":[62],"while":[63],"few":[64],"fail":[67],"bring":[69],"effects":[71],"recommendations.":[73],"To":[74],"assist":[75],"development":[77],"use":[79],"context-aware":[81,151],"capabilities,":[82],"we":[83],"propose":[84,109],"framework,":[86],"RCFS-CARS":[87,143],"uses":[89],"influential":[90],"contexts,":[91],"make":[92],"their":[93],"sets":[94],"with":[95],"appropriate":[96],"relaxation":[97],"applied":[100],"on":[101,131],"different":[102],"parts":[103],"algorithm.":[106],"We":[107],"also":[108],"strategy":[111],"detect":[113],"noisy":[115],"ratings":[116],"datasets":[119,133],"fix":[121],"refine":[124],"recommendation":[126,152],"results.":[127],"The":[128],"experimental":[129],"results":[130],"two":[132],"reveal":[134],"noise":[137],"detection":[138],"correction":[140],"process":[141],"method":[144],"is":[145],"much":[146],"superior":[147],"effective":[149],"scenarios.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}