History and asymmetric sierpinski carpet based employment recommendation

In recent years, with more and more college students graduating, the employment becomes a serious problem, which attracts more and more attention. Therefore, it is imperative to develop the platform for employment recommendation. The existing employment recommendation systems only take into account several properties such as salary, employment description and the major of the applicant. However, they ignored the history information and didn´t analyze the students that have been employed previously. To address this problem, this paper proposed a history and asymmetric sierpinski carpet based employment recommendation system. This system first analyzes the similarity between companies according to the history of their staff information. Then the asymmetric sierpinski carpet is used as a layout algorithm to visualize the recommendations. In addition, several interaction techniques are developed to adjust the visualization process. Finally, this paper implements an experiment to argue that our work is feasible and effective.