SLIIT >
Research Symposium >
SLIIT Student Research -2017 >

Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/470

Title: Employee Turnover Prediction Browsing history and HR data
Authors: Viran Pravinda, H.I.
Sathyani, G.D.M.S.
Kavinda, T.D.C.
Perera, M.A.P.I.
Wijesundara, Malitha
Keywords: Web Browsing History
HR data
Issue Date: 2017
Publisher: SLIIT
Series/Report no.: ;17-052
Abstract: Employees are the most valuable asset that a company can have without any doubt. Keeping a high valued and skillful employee within a company will be beneficial for the well-being of a company. Employees quitting the company will be the downfall of that company. Therefore, it is better if the higher management of a company can predict whether an employee is going to leave the company or not and try to keep him/her within the company. In this paper, we have briefly discussed how to achieve the above prediction using an employee’s emails, call logs, web browsing history and HR data. Moreover, data mining techniques that we used to get the prediction from each and every component will be discussed.
URI: http://hdl.handle.net/123456789/470
Appears in Collections:SLIIT Student Research -2017

Files in This Item:

File Description SizeFormat
17-052.pdf458.1 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback