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Research and Advanced Technology for Digital Libraries

Volume 6966 of the series Lecture Notes in Computer Science pp 15-26

How to Become a Group Leader? or Modeling Author Types Based on Graph Mining

  • George TsatsaronisAffiliated withCarnegie Mellon UniversityBiotechnology Center (BIOTEC), Technische Universität Dresden
  • , Iraklis VarlamisAffiliated withCarnegie Mellon UniversityDept. of Informatics and Telematics, Harokopio University of Athens
  • , Sunna TorgeAffiliated withCarnegie Mellon UniversityBiotechnology Center (BIOTEC), Technische Universität Dresden
  • , Matthias ReimannAffiliated withCarnegie Mellon UniversityBiotechnology Center (BIOTEC), Technische Universität Dresden
  • , Kjetil NørvågAffiliated withCarnegie Mellon UniversityDept. of Computer and Information Science, NTNU
  • , Michael SchroederAffiliated withCarnegie Mellon UniversityBiotechnology Center (BIOTEC), Technische Universität Dresden
  • , Matthias ZschunkeAffiliated withCarnegie Mellon UniversityBiotechnology Center (BIOTEC), Technische Universität Dresden

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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.

Keywords

Power Graph Analysis Authors’ Clustering Graph Mining