{"id":"https://openalex.org/W2942098650","doi":"https://doi.org/10.29007/3xfj","title":"A Novel Neighborhood Calculation Method by Assessing Users' Varying Preferences in Collaborative Filtering","display_name":"A Novel Neighborhood Calculation Method by Assessing Users' Varying Preferences in Collaborative Filtering","publication_year":2019,"publication_date":"2019-03-13","ids":{"openalex":"https://openalex.org/W2942098650","doi":"https://doi.org/10.29007/3xfj","mag":"2942098650"},"language":"en","primary_location":{"id":"doi:10.29007/3xfj","is_oa":true,"landing_page_url":"https://doi.org/10.29007/3xfj","pdf_url":"https://easychair.org/publications/open/glDL","source":{"id":"https://openalex.org/S4220651395","display_name":"EPiC series in computing","issn_l":"2398-7340","issn":["2398-7340"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPiC Series in Computing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://easychair.org/publications/open/glDL","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101908918","display_name":"Pradeep Kumar Singh","orcid":"https://orcid.org/0000-0002-9504-1504"},"institutions":[{"id":"https://openalex.org/I155837530","display_name":"National Institute of Technology Durgapur","ror":"https://ror.org/04ds0jm32","country_code":"IN","type":"education","lineage":["https://openalex.org/I155837530"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pradeep Kumar Singh","raw_affiliation_strings":["Dept. of Computer Science and Engineering, National Institute of Technology Durgapur , India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Engineering, National Institute of Technology Durgapur , India","institution_ids":["https://openalex.org/I155837530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075023855","display_name":"Pijush Kanti Dutta Pramanik","orcid":"https://orcid.org/0000-0001-9438-9309"},"institutions":[{"id":"https://openalex.org/I155837530","display_name":"National Institute of Technology Durgapur","ror":"https://ror.org/04ds0jm32","country_code":"IN","type":"education","lineage":["https://openalex.org/I155837530"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pijush Kanti Dutta Pramanik","raw_affiliation_strings":["Dept. of Computer Science and Engineering, National Institute of Technology Durgapur , India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Engineering, National Institute of Technology Durgapur , India","institution_ids":["https://openalex.org/I155837530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111936306","display_name":"Narayan C. Debnath","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142079","display_name":"Eastern International University","ror":"https://ror.org/03gvjya19","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210142079"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Narayan C. Debnath","raw_affiliation_strings":["School of Computing and Information Technology, Eastern International University, Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Information Technology, Eastern International University, Vietnam","institution_ids":["https://openalex.org/I4210142079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046112828","display_name":"Prasenjit Choudhury","orcid":"https://orcid.org/0000-0001-6687-3056"},"institutions":[{"id":"https://openalex.org/I155837530","display_name":"National Institute of Technology Durgapur","ror":"https://ror.org/04ds0jm32","country_code":"IN","type":"education","lineage":["https://openalex.org/I155837530"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Prasenjit Choudhury","raw_affiliation_strings":["Dept. of Computer Science and Engineering, National Institute of Technology Durgapur , India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Engineering, National Institute of Technology Durgapur , India","institution_ids":["https://openalex.org/I155837530"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5365,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.83488566,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"58","issue":null,"first_page":"345","last_page":"333"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.996999979019165,"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":0.996999979019165,"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":0.9546999931335449,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/movielens","display_name":"MovieLens","score":0.9581831693649292},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.9315453171730042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7609513998031616},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6818521618843079},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.6612528562545776},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6321362257003784},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.614617645740509},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5597911477088928},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5395672917366028},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4940233826637268},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34507620334625244},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31671178340911865},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15906399488449097}],"concepts":[{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.9581831693649292},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.9315453171730042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7609513998031616},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6818521618843079},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.6612528562545776},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6321362257003784},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.614617645740509},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5597911477088928},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5395672917366028},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4940233826637268},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34507620334625244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31671178340911865},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15906399488449097},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.29007/3xfj","is_oa":true,"landing_page_url":"https://doi.org/10.29007/3xfj","pdf_url":"https://easychair.org/publications/open/glDL","source":{"id":"https://openalex.org/S4220651395","display_name":"EPiC series in computing","issn_l":"2398-7340","issn":["2398-7340"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPiC Series in Computing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.29007/3xfj","is_oa":true,"landing_page_url":"https://doi.org/10.29007/3xfj","pdf_url":"https://easychair.org/publications/open/glDL","source":{"id":"https://openalex.org/S4220651395","display_name":"EPiC series in computing","issn_l":"2398-7340","issn":["2398-7340"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPiC Series in Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2942098650.pdf","grobid_xml":"https://content.openalex.org/works/W2942098650.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W1963771662","https://openalex.org/W2110325612","https://openalex.org/W2134834365","https://openalex.org/W2163406942","https://openalex.org/W2461635316","https://openalex.org/W2549180152","https://openalex.org/W2587697323","https://openalex.org/W2587994769","https://openalex.org/W2605814604","https://openalex.org/W2889611811","https://openalex.org/W2950332743"],"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/W2942098650"],"abstract_inverted_index":{"To":[0],"recommend":[1],"an":[2],"item":[3],"to":[4],"a":[5,71,114,124],"target":[6,49,115],"user,":[7],"Collaborative":[8],"Filtering":[9],"(CF)":[10],"considers":[11],"the":[12,23,27,31,35,37,45,48,73,82,98,104,110,128,133,145,148,154,160],"preferences":[13,58],"of":[14,22,29,40,47,57,65,76,89,103,113,153],"other":[15],"similar":[16,106],"users":[17,107,131],"or":[18],"neighbors.":[19,32],"The":[20,151],"accuracy":[21,146],"recommendation":[24],"depends":[25],"on":[26,118,159],"effectiveness":[28],"assessing":[30],"But":[33],"over":[34],"time,":[36],"mutual":[38],"likings":[39,102],"two":[41],"individuals":[42],"change;":[43],"hence,":[44],"neighbors":[46,77],"user":[50,116],"also":[51],"should":[52],"change.":[53],"However,":[54],"this":[55,92],"shifting":[56],"is":[59,157],"not":[60,79],"considered":[61],"by":[62,137],"traditional":[63],"methods":[64],"calculating":[66,109],"neighborhood":[67,84],"in":[68,101,132,147],"CF.":[69],"As":[70],"result,":[72],"calculated":[74],"set":[75],"does":[78],"always":[80],"reflect":[81],"optimal":[83],"at":[85],"any":[86],"given":[87],"point":[88],"time.":[90],"In":[91],"paper,":[93],"we":[94],"argue":[95],"for":[96],"considering":[97],"continuous":[99],"change":[100],"previous":[105],"and":[108,164,176],"neighbor-":[111],"hood":[112],"based":[117],"different":[119,134,167],"time":[120,135],"periods.":[121],"We":[122],"propose":[123],"method":[125],"that":[126],"assesses":[127],"similarity":[129],"between":[130],"period":[136],"using":[138,166],"K-means":[139],"clustering.":[140],"This":[141],"approach":[142],"significantly":[143],"improves":[144],"personalized":[149],"recommendation.":[150],"performance":[152,168],"proposed":[155],"algorithm":[156],"tested":[158],"MovieLens":[161],"datasets":[162],"(ml-100k":[163],"ml-1m)":[165],"metrics":[169],"viz.":[170],"MAE,":[171],"RMSE,":[172],"Precision,":[173],"Recall,":[174],"F-score,":[175],"accuracy.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}