Mining potential research synergies from co-authorship graphs using power graph analysis
International Journal of Web Engineering and Technology
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Visual analysis of knowledge domain is an emerging field of study as science is highly dynamic and constantly evolving. Behind the scene, a knowledge domain is formed and contributed by enormous researchers' publications that describe the common subject of the domain. There is large number of significant activities have been carried out to visualize and identify the knowledge domains of research projects, groups and communities. However, the research on visualizing the knowledge structure at individual level is relative inactive. It is difficult to track down the individual's contribution to the subject and the degree of the knowledge they possess. In this paper, we are attempting to visualize the individual's knowledge structure by analyzing the citation and co-authorship relational structures. We try to analyze and map author's documents to the knowledge domains. By mapping the documents to knowledge domain, we obtain the skeleton of knowledge structure of an individual. Then, we apply the visualization technique to present the result.