Design And Implementation Of Scalable University Ranking Management System

With the continuous development of social and economic, competition among colleges and universities is becoming increasingly fierce. It is more and more important to make evaluation on the level of a university through the various indicators and to predict the development of a university through the ranking over the years. Based on this demand, there are many outstanding ranking lists of universities in recent years. They measure the level and the development of the universities from the objective aspect professionally.The traditional ranking lists mostly exist in books or static pages. Their functions are unitary and they are non-scalable, so people always need to spend a lot of energy to collect, query and compare the data of every ranking list. Compared with the traditional presentation of the ranking list, the university ranking management system based on internet has a lot of characters such as scalable, easy to maintain, and easy to use. It can greatly reduce the inefficiency by too much artificial operation and also it can avoid the disadvantages of poor scalability. The goal of this paper is to research and implement a scalable university ranking management system based on SSH. Firstly, Struts, Spring, Hibernate framework are analyzed. Combined with their own characteristics and advantages, these three frameworks are integrated into a SSH multilayer frame. The design of the system surrounds the needs of the system closely. Taking the scalability and maintainability into consideration, the system is developed modularly and the function of the system is split in detail. It makes the function of the system expand greatly. This paper also describes the design and results of each module in detail, displays the implementation and testing of the various parts of the system as well.The design, development and use of the scalable university ranking management system based on SSH farewells the manually time-consuming way to view and analysis the university rankings completely. The system not only can fully fit the existing mainstream ranking list but also can be compatible with the unknown data and structure of the ranking list. The new idea proposed in this paper has very practical value for the inquiry, analysis and statistic of the university rankings.