Classification of characteristic words of electronic newspaper based on the directed relation

Newspaper articles are gradually opened to Web system. But the categories of articles are remained in conventional category types. So users of these system have to consider the appropriate searching keywords and categories when they search some articles. In this paper, we propose the new classification method for the characteristic words based on directed relation. We think this classification can change categories of articles and accessing keywords of users. First, we introduce the word vector and directed relation degree. Second, we define the classification method, reference degree and abstraction method of cluster. Finally, we experimented using one month data and can get the following results. (1)Both directional tightly connected words are suitable base words of clusters of articles. (2)Level-0 abstraction method can draw the rough border of clusters. (3)One directional tightly connected words represent the main general words or proper words.