Development of a Job Applicants E-government System Based on Web Mining Classification Methods

Rasha Hani  Salman; Nadia Adnan  Shiltagh; Mahmood Zaki  Abdullah

doi:10.24996/ijs.2021.62.8.28

Authors

Rasha Hani Salman Informatics Institute for Postgraduate Studies, Iraqi Commission for Computer & informatics, Baghdad , Iraq
Nadia Adnan Shiltagh University of Baghdad, College of Engineering ,Baghdad – Iraq
Mahmood Zaki Abdullah Mustansiriyah University, College of Engineering, Baghdad – Iraq

DOI:

https://doi.org/10.24996/ijs.2021.62.8.28

Keywords:

Data Mining, Web Mining, Web Content Mining, prediction, classification algorithms

Abstract

Governmental establishments are maintaining historical data for job applicants for future analysis of predication, improvement of benefits, profits, and development of organizations and institutions. In e-government, a decision can be made about job seekers after mining in their information that will lead to a beneficial insight. This paper proposes the development and implementation of an applicant's appropriate job prediction system to suit his or her skills using web content classification algorithms (Logit Boost, j48, PART, Hoeffding Tree, Naive Bayes). Furthermore, the results of the classification algorithms are compared based on data sets called "job classification data" sets. Experimental results indicated that the algorithm j48 had the highest precision (94.80%) compared to other algorithms for the aforementioned dataset.