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Abstract-XML is an important standard of information representation and data exchange over the Internet, document classification is an important way to get useful information from the mass of information solutions, a method of XML document classification is proposed based on fuzzy matching path in the paper. First, the information that has no influence on the classification is removed; Then a mixed method is used to compute XML document similarity, XML document is expressed as a collection of path, deleting the recurring and matching fuzzy path in order to improve efficiency, Hungarian algorithm to calculate the similarity between documents; Finally, 2 experiments are done and the results show that the method is effective.

Abstract.A credit system is the inexorable trend of higher education development. Course selection is the basis and core. Therefore, it is necessary to establish a reasonable course recommendation system. A method to recommend the course is used to guide students to choose the right course based on a large number of grades in the educational management system, and the K nearest neighbors are chosen to estimate score based on similarities between the student and the others. Reducing the attribute of datasets is one of the core contents in rough set theory. Remove the attributes that are not as important or redundant in knowledge property to improve the efficiency. The method is applied to the prediction of student grades using 3 different methods to discrete scores, the results show that the equal frequency algorithm is better than the others methods.

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