Applying Clustering Methods in Drawing Maps of Science: Case Study of the Map For Urban Management Science

Abstract

The present paper offers a basic introduction to data clustering and demonstrates the application of clustering methods in drawing maps of science. All approaches towards classification and clustering of information are briefly discussed. Their application to the process of visualization of conceptual information and drawing of science maps are illustrated by reviewing similar researches in this field. By implementing aggregated hierarchical clustering algorithm, which is an algorithm based on complete-link method, the map for urban management science as an emerging, interdisciplinary scientific field is analyzed and reviewed.

Keywords

• information clustering; scientometry; science maps; urban management sciene