The Research Of Ontology Technology And Decision Tree Algorithm And Using Them To Apply In The College Teaching Management

At present, the broadening amount of college, the traditional college educational management pattern can rarely meet the actual requirements. How to use the resource reasonable to develop college is a problem of college teaching management. Classification rules can supply decisions such as arranging curriculum, enrolling of the proportion of male and female students. The decisions play a certain role in promoting high school to a further development in information age. The main works of the text are summarized as follows:In this passage, its study objects are the ontology and the decision tree algorithm. The first, the paper detaily studies the definition of Ontology, Ontology description language, Ontology construction method, Ontology applications, the hot of ontology research at present, as well as the direction of future research. Ontology Construction Technology can be used to Creat College Teaching Management Knowledge Model. And for the Grade Relevance Knowledge Model of teaching management it has been done a fairly study. The second, from the background of the decision tree algorithm, the passage has researched and compared the all kinds of decision tree classification algorithms. It investigates the future research direction of the Decision Tree Algorithm. It studies the the ID3 Algorithm principle, which is the one of the Decision Tree Algorithm, and it also improve the ID3 Algorithm based on the Test attribute root node. At last, the passage uses ID3 Algorithm and approved ID3 Algorithm to analysis the Grade Relevance Knowledge Model based on Ontology Technology. The text mainly introduces the OWL ontology language of W3C and ontology creation tools of protege. Using Relational database as an intermediary, it studies how to map the text data in the Grade Relevance into the relational database, then it analyses datas based on algorithm to draw classification rules. Founding Classification rules drawn by the improved algorithm meet reality more. It illustrates improved algorithm advantages.