The objective of this study is to use a clustering algorithm based on journal cross-citation to validate and to improve the
journal-based subject classification schemes. The cognitive structure based on the clustering is visualized by the journal
cross-citation network and three kinds of representative journals in each cluster among the communication network have been
detected and analyzed. As an existing reference system the 15-field subject classification by Glänzel and Schubert (Scientometrics
56:55–73, <cite>2003</cite>) has been compared with the clustering structure.