TY - GEN
T1 - Visualizing bibliographic databases as graphs and mining potential research synergies
AU - Varlamis, Iraklis
AU - Tsatsaronis, George
PY - 2011
Y1 - 2011
N2 - Bibliographic databases are a prosperous field for data mining research and social network analysis. They contain rich information, which can be analyzed across different dimensions (e.g., author, year, venue, topic) and can be exploited in multiple ways. The representation and visualization of bibliographic databases as graphs and the application of data mining techniques can help us uncover interesting knowledge concerning potential synergies between researchers, possible matchings between researchers and venues, or even the ideal venue for presenting a research work. In this paper, we propose a novel representation model for bibliographic data, which combines coauthorship and content similarity information, and allows for the formation of scientific networks. Using a graph visualization tool from the biological domain, we are able to provide comprehensive visualizations that help us uncover hidden relations between authors and suggest potential synergies between researchers or groups.
AB - Bibliographic databases are a prosperous field for data mining research and social network analysis. They contain rich information, which can be analyzed across different dimensions (e.g., author, year, venue, topic) and can be exploited in multiple ways. The representation and visualization of bibliographic databases as graphs and the application of data mining techniques can help us uncover interesting knowledge concerning potential synergies between researchers, possible matchings between researchers and venues, or even the ideal venue for presenting a research work. In this paper, we propose a novel representation model for bibliographic data, which combines coauthorship and content similarity information, and allows for the formation of scientific networks. Using a graph visualization tool from the biological domain, we are able to provide comprehensive visualizations that help us uncover hidden relations between authors and suggest potential synergies between researchers or groups.
UR - https://www.scopus.com/pages/publications/80052710806
U2 - 10.1109/ASONAM.2011.52
DO - 10.1109/ASONAM.2011.52
M3 - Contribución a la conferencia
AN - SCOPUS:80052710806
SN - 9780769543758
T3 - Proceedings - 2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011
SP - 53
EP - 60
BT - Proceedings - 2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011
PB - IEEE Computer Society
ER -