A Topic Finding Method for Scientific and Technical Literature

Scientific and technical literature is a useful resource where people can extract interesting knowledge or patterns by text mining tools. Text mining technologies have been widely used to reveal topics and the structure of topics. In this paper, the selected articles in the form of textual data are represented by the network structure at first, and then text clustering algorithm is applied to the process of the scientific and technical literature in the field of management taken from CNKI in years from 1984 to 2009 and clusters are obtained eventually. Further, the method of social network analysis is adopted to do the further analysis. The similarities of clusters of every two years are calculated to find communities and topics. It is very useful not only to find topics in management area and the relations between topics but also to achieve the literature referred to one topic in which we are interested.