{"id":"https://openalex.org/W3171927037","doi":"https://doi.org/10.1109/syscon48628.2021.9447139","title":"Deploying Different Clustering Techniques on a Collaborative-based Movie Recommender","display_name":"Deploying Different Clustering Techniques on a Collaborative-based Movie Recommender","publication_year":2021,"publication_date":"2021-04-15","ids":{"openalex":"https://openalex.org/W3171927037","doi":"https://doi.org/10.1109/syscon48628.2021.9447139","mag":"3171927037"},"language":"en","primary_location":{"id":"doi:10.1109/syscon48628.2021.9447139","is_oa":false,"landing_page_url":"https://doi.org/10.1109/syscon48628.2021.9447139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Systems Conference (SysCon)","raw_type":"proceedings-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/A5082724003","display_name":"Dina Nawara","orcid":"https://orcid.org/0000-0002-0302-8012"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Dina Nawara","raw_affiliation_strings":["Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079953122","display_name":"Rasha Kashef","orcid":"https://orcid.org/0000-0002-3430-1536"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Rasha Kashef","raw_affiliation_strings":["Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5082724003"],"corresponding_institution_ids":["https://openalex.org/I530967"],"apc_list":null,"apc_paid":null,"fwci":4.2661,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.94574882,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9976999759674072,"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":0.9976999759674072,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9832000136375427,"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"}},{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9747999906539917,"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/collaborative-filtering","display_name":"Collaborative filtering","score":0.8618651032447815},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8573908805847168},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.8218775987625122},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7888171076774597},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.6156654357910156},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5947684645652771},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4897191822528839},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"k-means clustering","score":0.46573036909103394},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41322576999664307},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3505690097808838},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.34385281801223755},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.2967943549156189},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11774730682373047},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10804250836372375}],"concepts":[{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.8618651032447815},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8573908805847168},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8218775987625122},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7888171076774597},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.6156654357910156},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5947684645652771},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4897191822528839},{"id":"https://openalex.org/C207968372","wikidata":"https://www.wikidata.org/wiki/Q310401","display_name":"k-means clustering","level":3,"score":0.46573036909103394},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41322576999664307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3505690097808838},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.34385281801223755},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.2967943549156189},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11774730682373047},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10804250836372375}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/syscon48628.2021.9447139","is_oa":false,"landing_page_url":"https://doi.org/10.1109/syscon48628.2021.9447139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Systems Conference (SysCon)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1574580469","https://openalex.org/W2000764607","https://openalex.org/W2057923756","https://openalex.org/W2061572266","https://openalex.org/W2080918732","https://openalex.org/W2084512860","https://openalex.org/W2122209504","https://openalex.org/W2185184584","https://openalex.org/W2203920572","https://openalex.org/W2248517341","https://openalex.org/W2268856018","https://openalex.org/W2270192120","https://openalex.org/W2278485349","https://openalex.org/W2339853937","https://openalex.org/W2349932203","https://openalex.org/W2386126672","https://openalex.org/W2398374871","https://openalex.org/W2497122656","https://openalex.org/W2536671271","https://openalex.org/W2540336133","https://openalex.org/W2591489252","https://openalex.org/W2596285588","https://openalex.org/W2618416470","https://openalex.org/W2620456568","https://openalex.org/W2733722625","https://openalex.org/W2734804095","https://openalex.org/W2735369391","https://openalex.org/W2736209431","https://openalex.org/W2794007675","https://openalex.org/W2807361518","https://openalex.org/W2944126511","https://openalex.org/W2965805264","https://openalex.org/W2994068021","https://openalex.org/W3007058738","https://openalex.org/W3008323760","https://openalex.org/W3023190967","https://openalex.org/W3087872637","https://openalex.org/W3090540127","https://openalex.org/W3091769066","https://openalex.org/W3097103183","https://openalex.org/W3098789548","https://openalex.org/W6634414642","https://openalex.org/W6665812150"],"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":{"Recommendation":[0,15],"systems":[1,16],"are":[2],"involved":[3],"in":[4],"many":[5],"industries,":[6],"for":[7,78,166],"example":[8],"(e-health,":[9],"transportation,":[10],"e-commerce,":[11],"and":[12,22,74,94,98,118,158,168],"agriculture),":[13],"where":[14],"aim":[17],"to":[18,39,109],"benefit":[19],"both":[20],"market":[21],"user":[23],"levels.":[24],"They":[25],"help":[26],"consumers":[27],"make":[28],"the":[29,76,133,137,142,159],"right":[30],"decision":[31],"based":[32,50,135],"on":[33,51,132,136],"their":[34],"preferences":[35],"without":[36],"being":[37],"exposed":[38],"data":[40],"overload.":[41],"Nowadays,":[42],"there":[43],"is":[44],"a":[45,79],"wide":[46],"range":[47],"of":[48,103],"recommenders":[49],"different":[52,84,111],"filtering":[53,61],"approaches,":[54],"such":[55,87,114,147],"as":[56,88,115,148],"Collaborative-based,":[57],"Content-based,":[58],"hybrid-based,":[59],"demographic-based":[60],"approaches.":[62,121],"In":[63],"this":[64],"paper,":[65],"we":[66],"present":[67],"clustering-based":[68],"recommendation":[69],"systems.":[70],"We":[71,107,122,140],"also":[72],"experiment":[73],"show":[75],"results":[77],"collaborative-based":[80],"movie":[81],"recommender":[82],"using":[83,96,144],"clustering":[85,112,120,130],"techniques":[86,131],"Kmeans,":[89],"BIRCH":[90],"Balanced":[91],"Iterative":[92],"Reducing":[93],"Clustering":[95,102],"Hierarchies)":[97],"DBSCAN":[99],"(Density-based":[100],"Spatial":[101],"Applications":[104],"with":[105],"Noise).":[106],"intended":[108],"choose":[110],"approaches":[113],"partitional,":[116],"hierarchical,":[117],"density-based":[119],"incorporated":[123],"Item-based":[124],"Collaborative":[125],"filtering,":[126],"then":[127],"applied":[128],"multiple":[129],"dataset":[134],"users'":[138],"ratings.":[139],"checked":[141],"performance":[143],"accuracy":[145],"measures":[146,163],"MAE":[149],"(Mean":[150],"Absolute":[151],"Error),":[152],"RMSE":[153],"(Root":[154],"mean":[155],"square":[156],"error),":[157],"computed":[160],"time.":[161],"These":[162],"were":[164],"calculated":[165],"analysis":[167],"comparison":[169],"purposes.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}
