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

Authors:
George Tsatsaronis;Iraklis Varlamis;Sunna Torge;Matthias Reimann;Kjetil Nørvåg;Michael Schroeder;Matthias Zschunke
Affiliations:
Biotechnology Center, Technische Universität Dresden, Germany;Dept. of Informatics and Telematics, Harokopio University of Athens, Greece;Biotechnology Center, Technische Universität Dresden, Germany;Biotechnology Center, Technische Universität Dresden, Germany;Dept. of Computer and Information Science, NTNU, Norway;Biotechnology Center, Technische Universität Dresden, Germany;Biotechnology Center, Technische Universität Dresden, Germany
Venue:
TPDL'11 Proceedings of the 15th international conference on Theory and practice of digital libraries: research and advanced technology for digital libraries
Year:
2011

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Abstract

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