A Score-based Human Resource Recommendation System

• Main Authors: Tzu-Hsin Chien, 簡姿欣
• Other Authors: Sheng-Lung Peng
• Format: Others
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/udqmu3

碩士 === 國立東華大學 === 資訊工程學系 === 102 === Abstract "People" is the most valuable and unique assets in companies. Good human resources policy will help to enhance the value of the company. With the development of Internet, more people through the way to find a job from Job Bank Website. In such a way, it not only breaks the limitation of time and space, but also provides a convenient and fast pipeline for job seekers. However, in the current Job Bank Website, there are rarely analyzed students’ course records when freshmen searched jobs. Enterprise picks out a suitable talented person among data of many job seekers. It will be a big test in the process of searching talented person. In this thesis, we propose a Human Resource Recommendation System. The objects of this thesis are fresh graduated students from universities. For these fresh men, only course records can be shown. Thus, propose a mapping function to map students’ raw data to required expertise and skills of enterprises. Finally, our recommendation system recommends a list of suitable talented persons to the seekers.