The Study Of Subsidy Systecm On Poor Studeius

In China，poverty stricken students in Colleges have always been highlyconcerned about the party and government．In order to ensure that the poverty strickenstudents in Colleges can complete their studies successfully，the state raised a lot offunding policy．In order to implement these funding policy into place，the work ofidentifying becomes very important．The paper studies an efficient subsidization system which is realized bycomputer and statistical knowledge for the poverty-stricken students．So we can gradethe poor students to different levels sketchily, and ultimately determine the level ofpoor students by democratic appraisal．The system has great practical value in thesubsidization system of colleges，which has passed the testing phase,entered thepractical stage．The system data is divided into the attribute information and textinformation．There are different methods which contain Native Bayesian，Decisiontrees as the underlying Random forests,Vector machines and so on．These methodsare used to attribute information．This paper focuses on the Native Bayesian．For textmessages，this paper does a lot of pre-processing works which include updating theoriginal thesaurus and designing specific thesaurus poor students．From the point of view of the characteristics of the text，the paper builds a textdata simulation model，which is a new model and has not been described in anyliterature．Application of the model can produce some word，and construct a similardata with real text． The text data has high maneuverability and well datavisualization．So we can simulate and analysis the text data, and then found efficientmethod that used in real data categorization for handling the text categorization．...