How to become a group leader? or modeling author types based on graph mining

摘要: Bibliographic databases are a prosperous field for data mining research and social network analysis. The representation visualization of bibliographic as graphs the application techniques can help us uncover interesting knowledge regarding how publication records authors evolve over time. In this paper we propose novel methodology to model bibliographical Power Graphs, mine them in an unsupervised manner, order learn basic author types their properties through clustering. takes into account evolution co-authorship information, volume published papers time, well impact factors venues hosting respective publications. As proof concept applicability scalability our approach, present experimental results DBLP data.