{"id":"https://openalex.org/W3184413218","doi":"https://doi.org/10.1109/siu53274.2021.9477897","title":"A Comparative Study for Employee Churn Prediction","display_name":"A Comparative Study for Employee Churn Prediction","publication_year":2021,"publication_date":"2021-06-09","ids":{"openalex":"https://openalex.org/W3184413218","doi":"https://doi.org/10.1109/siu53274.2021.9477897","mag":"3184413218"},"language":"en","primary_location":{"id":"doi:10.1109/siu53274.2021.9477897","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu53274.2021.9477897","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5040793150","display_name":"Musa Berat Bahadir","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Musa Berat Bahad\u0131r","raw_affiliation_strings":["Araşturma ve İnovasyon, Ata Teknoloji Platformları,İstanbul,Türkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Araşturma ve İnovasyon, Ata Teknoloji Platformları,İstanbul,Türkiye","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012244756","display_name":"Ahmet Tu\u011frul Bayrak","orcid":"https://orcid.org/0009-0009-6043-2765"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahmet Tu\u011frul Bayrak","raw_affiliation_strings":["Araşturma ve İnovasyon, Ata Teknoloji Platformları,İstanbul,Türkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Araşturma ve İnovasyon, Ata Teknoloji Platformları,İstanbul,Türkiye","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5097107181","display_name":"G\u00fcven Y\u00fccet\u00fcrk","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G\u00fcven Y\u00fccet\u00fcrk","raw_affiliation_strings":["Araşturma ve İnovasyon, Ata Teknoloji Platformları,İstanbul,Türkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Araşturma ve İnovasyon, Ata Teknoloji Platformları,İstanbul,Türkiye","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5097078926","display_name":"P\u0131nar Ergun","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132454","display_name":"National Nuclear Research Center","ror":"https://ror.org/03g11f026","country_code":"AZ","type":"facility","lineage":["https://openalex.org/I4210132454"]}],"countries":["AZ"],"is_corresponding":false,"raw_author_name":"P\u0131nar Ergun","raw_affiliation_strings":["İnsan Kaynaklari, Ata Teknoloji Platformları,İstanbul,Türkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"İnsan Kaynaklari, Ata Teknoloji Platformları,İstanbul,Türkiye","institution_ids":["https://openalex.org/I4210132454"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13812","display_name":"AI and HR Technologies","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13812","display_name":"AI and HR Technologies","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9933000206947327,"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/scope","display_name":"Scope (computer science)","score":0.7525721788406372},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6111540198326111},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5608404278755188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5428495407104492},{"id":"https://openalex.org/keywords/turnover","display_name":"Turnover","score":0.4180355370044708},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.40595918893814087},{"id":"https://openalex.org/keywords/management","display_name":"Management","score":0.08578503131866455},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.07953217625617981}],"concepts":[{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.7525721788406372},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6111540198326111},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5608404278755188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5428495407104492},{"id":"https://openalex.org/C26077564","wikidata":"https://www.wikidata.org/wiki/Q1910318","display_name":"Turnover","level":2,"score":0.4180355370044708},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.40595918893814087},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.08578503131866455},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.07953217625617981},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu53274.2021.9477897","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu53274.2021.9477897","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5400000214576721,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1525345465","https://openalex.org/W2048244076","https://openalex.org/W2064675550","https://openalex.org/W2297422159","https://openalex.org/W2510388300","https://openalex.org/W2518963095","https://openalex.org/W2621216181","https://openalex.org/W2743595002","https://openalex.org/W2767195638","https://openalex.org/W2769002462","https://openalex.org/W2770481292","https://openalex.org/W2805391180","https://openalex.org/W2895760214","https://openalex.org/W2901532222","https://openalex.org/W2939488985","https://openalex.org/W2940100101","https://openalex.org/W3090045915","https://openalex.org/W3099255235","https://openalex.org/W3134276895"],"related_works":["https://openalex.org/W4241523039","https://openalex.org/W178231042","https://openalex.org/W2360028903","https://openalex.org/W4280543773","https://openalex.org/W2366083136","https://openalex.org/W2387622493","https://openalex.org/W1932132538","https://openalex.org/W2357832196","https://openalex.org/W1566252468","https://openalex.org/W4200375594"],"abstract_inverted_index":{"Employees":[0],"are":[1],"one":[2],"of":[3,8],"the":[4,53,61,73,77],"most":[5],"critical":[6],"elements":[7],"companies.":[9,18],"Unexpected":[10],"employee":[11,47,111],"turnover":[12],"causes":[13],"a":[14,102],"huge":[15],"cost":[16],"for":[17,34,104],"The":[19],"new":[20],"recruitment":[21],"process":[22],"not":[23],"only":[24],"consumes":[25],"money":[26],"and":[27,68],"time,":[28],"but":[29],"it":[30],"also":[31],"takes":[32],"time":[33],"newly":[35],"hired":[36],"employees":[37,54],"to":[38,106],"contribute":[39],"effectively.":[40],"In":[41,76],"this":[42],"study,":[43,89],"we":[44,64,79],"did":[45],"an":[46,82],"churn":[48],"analysis":[49],"that":[50],"predicts":[51],"whether":[52],"will":[55],"leave":[56],"their":[57],"current":[58],"company.":[59],"Within":[60],"study's":[62],"scope,":[63],"have":[65,80],"trained":[66],"standard":[67],"sequential":[69],"models,":[70],"then":[71],"compared":[72],"models'":[74],"successes.":[75],"end,":[78],"created":[81],"ensemble":[83],"model":[84],"from":[85],"successful":[86],"models.":[87],"This":[88],"which":[90],"is":[91],"carried":[92],"out":[93],"with":[94,109],"sample":[95],"Kaggle":[96],"data,":[97],"can":[98],"be":[99,107],"used":[100],"as":[101],"preliminary":[103],"studies":[105],"done":[108],"real":[110],"data.":[112]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}