DocumentCode :
2646308
Title :
Soft skills recommendation systems for IT jobs: A Bayesian network approach
Author :
Bakar, Afarulrazi Abu ; Ting, Choo-Yee
Author_Institution :
Software Dev. Lab., MIMOS Berhad, Bukit Jalil, Malaysia
fYear :
2011
fDate :
28-29 June 2011
Firstpage :
82
Lastpage :
87
Abstract :
Today, soft skills are crucial factors to the success of a project. For a certain set of jobs, soft skills are often considered more crucial than the hard skills or technical skills, in order to perform the job effectively. However, it is not a trivial task to identify the appropriate soft skills for each job. In this light, this study proposed a solution to assist employers when preparing advertisement via identification of suitable soft skills together with its relevancy to that particular job title. Bayesian network is employed to solve this problem because it is suitable for reasoning and decision making under uncertainty. The proposed Bayesian Network is trained using a dataset collected via extracting information from advertisements and also through interview sessions with a few identified experts.
Keywords :
Bayes methods; belief networks; business data processing; human resource management; recommender systems; Bayesian network approach; IT job; advertisement via identification; employer assistance; hard skill; soft skill recommendation system; technical skill; Accuracy; Bayesian methods; Interviews; Qualifications; Software; Testing; Training; Bayesian Network; Data Mining; Soft Skills;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining and Optimization (DMO), 2011 3rd Conference on
Conference_Location :
Putrajaya
ISSN :
2155-6938
Print_ISBN :
978-1-61284-211-0
Electronic_ISBN :
2155-6938
Type :
conf
DOI :
10.1109/DMO.2011.5976509
Filename :
5976509
Link To Document :
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