| Nowadays, the periodical industry has entered the stage of digital and networked period. Journal editing system is widely used. However, it has some shortage in intelligent management area, such as it can not automatic match reviewer experts, get reminder trial information in sometime, in lack of statistical analysis function for system data. Operators only handle out passively, without actively participating in process of periodical development planning and decision support.Aiming at the periodical editorial department, an aided support decision system for thesis approximations is designed and realized. The system active extracts key words through relationship between data forms in back-end database. They are bindinged to the corresponding controls. Hidden data are displayed, which facilitates the administrator’s operations. Regard date as core object, reviewer deadlines are generated at the same time of reviewer sending. After reviewer time limit is chosen, urge reviewer information set can be gotten by choose function. Sum number of the theses can be displayed which meets the choose case. Related data are imported to the statistical analysis software. Thus decision makers can make the next step planning with dependent forms and graphs.This paper analyzes the status of periodical industry’s information technology at home and abroad, raises the inadequate, throws out the ideas, describes exploitation tools and theories. Some methods about data mining are used to illustrate one experiment. The result and analysis is proposed. In the system development area, begin with the demand analysis, database design, system design as well as techniques of the programming design are described in detail. In the end, the system is run and the specific function is explained.Experimental result shows that the system presented can effectively compensate for the shortcomings and deficiencies of the existing systems, and it is suitable for application to practice. |
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