{"id":"https://openalex.org/W3120082291","doi":"https://doi.org/10.1109/ieem45057.2020.9309941","title":"Business Applications for Current Developments in Big Data Clustering: An Overview","display_name":"Business Applications for Current Developments in Big Data Clustering: An Overview","publication_year":2020,"publication_date":"2020-12-14","ids":{"openalex":"https://openalex.org/W3120082291","doi":"https://doi.org/10.1109/ieem45057.2020.9309941","mag":"3120082291"},"language":"en","primary_location":{"id":"doi:10.1109/ieem45057.2020.9309941","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem45057.2020.9309941","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","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/A5074790103","display_name":"G. Hass","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"G. Hass","raw_affiliation_strings":["Ivey Business School, Western University, London, Ontario, Canada"],"affiliations":[{"raw_affiliation_string":"Ivey Business School, Western University, London, Ontario, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004039843","display_name":"Phil Simon","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"P. Simon","raw_affiliation_strings":["Ivey Business School, Western University, London, Ontario, Canada"],"affiliations":[{"raw_affiliation_string":"Ivey Business School, Western University, London, Ontario, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"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":"R. Kashef","raw_affiliation_strings":["Ryerson University, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"Ryerson University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074790103"],"corresponding_institution_ids":["https://openalex.org/I125749732"],"apc_list":null,"apc_paid":null,"fwci":1.4951,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.86843192,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"195","last_page":"199"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9973999857902527,"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"}},"topics":[{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9973999857902527,"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"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9922999739646912,"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/big-data","display_name":"Big data","score":0.8818844556808472},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7165470123291016},{"id":"https://openalex.org/keywords/headline","display_name":"Headline","score":0.7008877992630005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6818798780441284},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.6700008511543274},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.49158796668052673},{"id":"https://openalex.org/keywords/currency","display_name":"Currency","score":0.4115290641784668},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33335721492767334},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.1407715082168579},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1205369234085083}],"concepts":[{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.8818844556808472},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7165470123291016},{"id":"https://openalex.org/C2778689934","wikidata":"https://www.wikidata.org/wiki/Q1313396","display_name":"Headline","level":2,"score":0.7008877992630005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6818798780441284},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.6700008511543274},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.49158796668052673},{"id":"https://openalex.org/C141121606","wikidata":"https://www.wikidata.org/wiki/Q8142","display_name":"Currency","level":2,"score":0.4115290641784668},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33335721492767334},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.1407715082168579},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1205369234085083},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C112698675","wikidata":"https://www.wikidata.org/wiki/Q37038","display_name":"Advertising","level":1,"score":0.0},{"id":"https://openalex.org/C556758197","wikidata":"https://www.wikidata.org/wiki/Q580018","display_name":"Monetary economics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieem45057.2020.9309941","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem45057.2020.9309941","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1566114229","https://openalex.org/W1633659671","https://openalex.org/W2001671710","https://openalex.org/W2003234666","https://openalex.org/W2039148220","https://openalex.org/W2052091171","https://openalex.org/W2057712948","https://openalex.org/W2063127047","https://openalex.org/W2078888611","https://openalex.org/W2088025572","https://openalex.org/W2095897464","https://openalex.org/W2126751256","https://openalex.org/W2166933393","https://openalex.org/W2170410701","https://openalex.org/W3041666796","https://openalex.org/W6633857196","https://openalex.org/W6636873521","https://openalex.org/W6684254493"],"related_works":["https://openalex.org/W4285135530","https://openalex.org/W2380567098","https://openalex.org/W2035489689","https://openalex.org/W906669285","https://openalex.org/W1553197492","https://openalex.org/W85886512","https://openalex.org/W1514610457","https://openalex.org/W1586468330","https://openalex.org/W3173716828","https://openalex.org/W2097747115"],"abstract_inverted_index":{"\"The":[0],"world's":[1],"most":[2],"valuable":[3],"resource":[4],"is":[5,26,36,44,148],"no":[6],"longer":[7],"oil,":[8],"but":[9],"data\"":[10],"announces":[11],"the":[12,15,23,47,51,96,128,131,143],"headline":[13],"of":[14,20,33,41,64,79,98,127,130,133,145],"May":[16],"6th,":[17],"2017":[18],"edition":[19],"The":[21,30,39],"Economist;":[22],"digital":[24],"revolution":[25],"here":[27],"to":[28],"stay.":[29],"primary":[31],"currency":[32],"this":[34,70,85,123],"movement":[35],"big":[37,42,86,109,146],"data.":[38,83],"complexity":[40],"data":[43,52,87,111,147],"defined":[45],"as":[46],"relationships":[48],"and":[49,102,120,136],"how":[50],"can":[53,74,88,105,113],"be":[54,106,114],"arranged":[55],"with":[56],"one":[57],"another.":[58],"Facebook":[59],"has":[60],"30":[61],"billion":[62],"pieces":[63],"unique":[65],"information":[66,104],"shared":[67],"each":[68],"month;":[69],"data's":[71],"sheer":[72],"size":[73],"cause":[75],"an":[76,125],"immeasurable":[77],"amount":[78],"combinations":[80],"for":[81,93],"relational":[82],"Analyzing":[84],"reveal":[89],"various":[90],"useful":[91],"insights":[92],"decision-makers.":[94],"With":[95],"adoption":[97,138],"clustering":[99,134],"analysis,":[100],"patterns":[101],"hidden":[103],"developed":[107],"from":[108],"raw":[110],"that":[112],"used":[115],"across":[116],"many":[117],"business":[118,140],"problems":[119],"applications.":[121],"In":[122],"paper,":[124],"overview":[126],"state":[129],"art":[132],"analysis":[135],"its":[137],"in":[139,142],"applications":[141],"era":[144],"presented.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}
