Text categorization method based on extension theory

We introduce a new text categorization method utilizing machine learning based on extension theory. This dependent degree based on the extension theory represents the extent to which the element belongs to the predefined categories. The "closeness degree" between the input document vector and standard range of each predefined category can be calculated. The new method is conceptually simple; it can be used with relatively low complexity and high flexibility: The algorithm is highly scalable. It can be effectively applied to text categorization, of which various features are consecutive values. Furthermore, this algorithm can be widely applied to computational linguistics.