Abstract: Location is one of the most important factors to consider when looking for offering a new job. Currently, there exist many job recommender systems to help match the right candidate with the right job. A review of the existing recommender systems, included within this article, reveals that there is an absence of appropriate mapping support offering for job recommendation. This article aims to propose a general map-based job recommender model, which is implemented and applied within a system for job seekers in Saudi Arabia. The system adapts content-based technique to recommend jobs using the cosine similarity and will help Saudi job seekers finding their desired job in an efficient way using interactive maps. This ultimately will contribute to Saudi Arabia moving forward to the digital transformation which is one of the major objectives to fulfill the Saudi vision 2030.

Manal Alghieth and Amal A. Shargabi. “A Map-based Job Recommender Model”. International Journal of Advanced Computer Science and Applications (IJACSA) 10.9 (2019). http://dx.doi.org/10.14569/IJACSA.2019.0100945

@article{Alghieth2019,
title = {A Map-based Job Recommender Model},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100945},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100945},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {9},
author = {Manal Alghieth and Amal A. Shargabi}
}