A clustering method using the strength of citation

Abstract

A new method for modelling and clustering a relational graph produced from the citation relation among scientific articles is discussed. One article corresponds to a point and a citation link corresponds to a directed walk in the graph. This graph is a direct-citation graph and a total-citation graph is derived from it. There exist two types of directed citation graph; i.e., citing directed-graph and cited directed-graph. The former is considered in this paper. These graphs are repre sented in the form of similarity matnces which are asymmetric. The characteristics of these graphs are analyzed by clustering. For this study, a research database was designed and produced to acquire bibliographic information and obtain relations be tween articles in it. A modelling methodology of its relational structure is described in this article. Combinatonal clustering methods have been examined and a clustering method for an asymmetric similarity matrix is also proposed.