Technical Papers Session V: An ontology-based knowledge management model for e-recruitment utilizing MOOCs data
Abstract/Description
In the recent past, the role and importance of Knowledge Management have become very visible in an organizational learning environment. This paper aims to cover the implementation of knowledge management in the process of development of e-recruitment platform using an ontology-based approach. The approach has been modeled in such a way that it can facilitate employers for hiring and recruiting purposes as per the organization's desired requirements with an effective utilization of MOOCs data. For the end-users, the developed ontology will be able to recommend candidates to the e-recruiter based on the required functions of the job post, and similarly students or eligible candidates who have completed MOOC will be able to view job vacancies based on their field of interest. The proposed model also incorporates the data of students, including the required information about the enrollment, grades, and skills attained in various MOOCs.
Keywords
Location
Lecture Hall B (Aman Tower, 11th floor)
Session Theme
Technical Papers Session V - Social Computing & Information Retrieval
Session Type
Parallel Technical Session
Session Chair
Dr. Tariq Rahim Soomro
Start Date
17-11-2019 2:20 PM
End Date
17-11-2019 2:40 PM
Recommended Citation
Javed, Z., Qazi, H., & Khoja, S. A. (2019). Technical Papers Session V: An ontology-based knowledge management model for e-recruitment utilizing MOOCs data. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2019/2019/38
COinS
Technical Papers Session V: An ontology-based knowledge management model for e-recruitment utilizing MOOCs data
Lecture Hall B (Aman Tower, 11th floor)
In the recent past, the role and importance of Knowledge Management have become very visible in an organizational learning environment. This paper aims to cover the implementation of knowledge management in the process of development of e-recruitment platform using an ontology-based approach. The approach has been modeled in such a way that it can facilitate employers for hiring and recruiting purposes as per the organization's desired requirements with an effective utilization of MOOCs data. For the end-users, the developed ontology will be able to recommend candidates to the e-recruiter based on the required functions of the job post, and similarly students or eligible candidates who have completed MOOC will be able to view job vacancies based on their field of interest. The proposed model also incorporates the data of students, including the required information about the enrollment, grades, and skills attained in various MOOCs.
