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Statistics report
Apr. 2021
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 83
Paper Published : 4548
No. of Authors : 9366
  Journal Paper


Paper Title :
Machine Learning Approach to Analyze Employee Dissatisfaction

Author :Divya Manoj, Richa Jaisinghani, Shruti Singh, Srishti Sewatkar, Sujata Khedkar

Article Citation :Divya Manoj ,Richa Jaisinghani ,Shruti Singh ,Srishti Sewatkar ,Sujata Khedkar , (2020 ) " Machine Learning Approach to Analyze Employee Dissatisfaction " , International Journal of Management and Applied Science (IJMAS) , pp. 43-47, Volume-6,Issue-8

Abstract : Employee dissatisfaction can happen because of various factors of a company like a salary, work environment, growth in the company and many more. These factors may not be satisfactory for employees. This may lead to employees leaving the company, companies getting a bad reputation and losing their talented employees. The proposed system provides the solution by determining the aspect category which is the major cause of dissatisfaction among employees. This system can provide insight into the companies to focus on their downside and improve it. This can also help an outsider to analyze the company first and then decide to join. The proposed system works in three phases: the first phase deals with the pre-processing of text data, the second phase deals with the topic modeling approach to identify the main aspects to be considered and the third phase makes use of an ensemble algorithm for classifying review to its aspect category. Keywords - LDA, Ensemble Algorithm, NLP, Aspect Categorization

Type : Research paper

Published : Volume-6,Issue-8


DOIONLINE NO - IJMAS-IRAJ-DOIONLNE-17540   View Here

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