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

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review



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.


Original languageEnglish
Title of host publicationResearch and Advanced Technology for Digital Libraries - International Conference on Theory and Practice of Digital Libraries, TPDL 2011, Proceedings
PublisherSpringer, Berlin [u. a.]
Number of pages12
ISBN (print)9783642244681
Publication statusPublished - 2011

Publication series

SeriesLecture Notes in Computer Science, Volume 6966


TitleInternational Conference on Theory and Practice of Digital Libraries, TPDL 2011
Duration26 - 28 September 2011

External IDs

ORCID /0000-0003-2848-6949/work/141543343
ORCID /0000-0001-9756-6390/work/142250113



  • Authors' Clustering, Graph Mining, Power Graph Analysis

Library keywords