{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T23:59:43Z","timestamp":1784591983110,"version":"3.55.0"},"reference-count":40,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100010790","name":"ERASMUS + KA2 Projects \u201cInformation Technology Governance for Tunisian Universities\u201d","doi-asserted-by":"publisher","award":["561614-EPP-1-2015-1-ES-EPPKA2-CBHE-JP"],"award-info":[{"award-number":["561614-EPP-1-2015-1-ES-EPPKA2-CBHE-JP"]}],"id":[{"id":"10.13039\/501100010790","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3074559","type":"journal-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T04:39:28Z","timestamp":1618979968000},"page":"60447-60458","source":"Crossref","is-referenced-by-count":111,"title":["From Big Data to Deep Data to Support People Analytics for Employee Attrition Prediction"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4788-4475","authenticated-orcid":false,"given":"Nesrine Ben","family":"Yahia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jihen","family":"Hlel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1555-9726","authenticated-orcid":false,"given":"Ricardo","family":"Colomo-Palacios","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1111\/j.1468-0467.2009.00314.x"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.14254\/2071-8330.2014\/7-1\/11"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.10.013"},{"key":"ref32","article-title":"How to construct deep recurrent neural networks","author":"pascanu","year":"2013","journal-title":"arXiv 1312 6026"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1126\/science.1127647","article-title":"Reducing the dimensionality of data with neural networks","volume":"313","author":"hinton","year":"2006","journal-title":"Science"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.pan.a004868"},{"key":"ref37","first-page":"1","article-title":"Attrition issues and retention challenges of employees","volume":"3","author":"goswami","year":"2012","journal-title":"Int J Sci Eng Res"},{"key":"ref36","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203451","article-title":"Greedy function approximation: A gradient boosting machine","volume":"29","author":"friedman","year":"2001","journal-title":"Ann Statist"},{"key":"ref35","first-page":"18","article-title":"Classification and regression by randomForest","volume":"2","author":"liaw","year":"2002","journal-title":"R News"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-7687-1_252"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbusres.2016.08.010"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s10664-008-9102-8"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1038\/nmat4395"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.3390\/socsci8100273"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2020.113290"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/INNOVATIONS.2018.8605976"},{"key":"ref15","first-page":"145","article-title":"Predicting employee attrition using machine learning","volume":"3","author":"ganesh v aishwaryalakshmi","year":"2018","journal-title":"Int J Sci Res Comput Sci Eng Inf Technol"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01057-7_56"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/4140707"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1177\/0972262918821221"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-13-5934-7_29"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/21.97458"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1111\/1748-8583.12090"},{"key":"ref27","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"pedregosa","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref3","year":"2019","journal-title":"Amazon fr&#x2014;People Analytics in the era of big Data Changing the way you Attract Acquire Develop and Retain Talent&#x2014;Jean Paul Isson&#x2014;Livres"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2016.01.052"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1023\/B:STCO.0000035301.49549.88"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2018.08.002"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-13-9330-3_15"},{"key":"ref7","first-page":"33","article-title":"Human resource predictive analytics (HRPA) for HR management in organizations","volume":"5","author":"mishra","year":"2016","journal-title":"Int J Sci Technol Res"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/hfm.20509"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1108\/JOEPP-04-2020-0071"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.14569\/IJARAI.2016.050904"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICICI.2017.8365293"},{"key":"ref22","first-page":"2372","article-title":"Analysis of employee attrition and implementing a decision support system providing personalized feedback and observations","volume":"7","author":"shah","year":"2020","journal-title":"Critical Review"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01177-2_11"},{"key":"ref24","first-page":"2871","article-title":"Employee attrition prediction using logistic regression","volume":"8","author":"ponnuru","year":"2020","journal-title":"International Journal of Applied Science and Engineering Research"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.3390\/computers9040086"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s10844-020-00614-9"},{"key":"ref25","first-page":"7","article-title":"Employee attrition prediction system","volume":"7","author":"kakad","year":"2020","journal-title":"International Journal of Engineering and Innovative Technology"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09409047.pdf?arnumber=9409047","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:55:43Z","timestamp":1639770943000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9409047\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":40,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3074559","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}