The Research of Text Categorization Based on FP-Tree

Decision tree is a forecasting model with a tree shape. The way from the root node to the leaf node forms the rule that forecasts a class label to the object. But it is often used in the condition of having not too much attributes. And FP-tree is a fast and efficient structure to discover frequent pattern. The paper proposes a new fast method for categorization through FP-tree. It discovers frequent feature terms of documents and categories using FP-tree and then forms a class decision tree by using the top frequent feature term to be the test attributes. So the decision tree is used in text categorization by the frequent feature terms. Finally the paper gives the experiment and the analysis of the method.