A smart Geo-Location Job Recommender System Based on Social Media Posts

• Published in: 2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS) pp. 505 - 510
• Main Authors: Mughaid, Ala, Obeidat, Ibrahim, Hawashin, Bilal, AlZu'bi, Shadi, Aqel, Darah
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2019
• Subjects: Data mining; Employment; Geo-location services; NLP; Organizations; Recommender system; Recommender systems; Semantics; smart system; social media mining; Social networking (online)
• DOI: 10.1109/SNAMS.2019.8931854

Social networks in real life is growing quickly, Social media have become a day base use for most of Internet users, because of the huge amount of provided services. Social media shares users' thoughts and data through a virtual networks. The proposed work focuses on implementing a smart job seeking system based on client's geo-location. This work proposes a smart system that mines social media networks, such as Twitter and Facebook to match the best vacancy for the exact job seeker. The matches have been presented based on client's geo-locations, which are located by mining their social media posts history. This system overcomes recent such systems as it employs modern recommender methods, Geolocation concepts, and Natural Language Processing (NLP) together in social media for real life problem solution.