@inproceedings{Brandes:2002:VBN:509740.509765,
  abstract = {We describe a novel approach to visualize bibliographic networks that facilitates the simultaneous identification of clusters (e.g., topic areas) and prominent entities (e.g., surveys or landmark papers). While employing the landscape metaphor proposed in several earlier works, we introduce new means to determine relevant parameters of the landscape. Moreover, we are able to compute prominent entities, clustering of entities, and the landscape's surface in a surprisingly simple and uniform way. The effectiveness of our network visualizations is illustrated on data from the graph drawing literature.},
  acmid = {509765},
  address = {Aire-la-Ville, Switzerland, Switzerland},
  author = {Brandes, U. and Willhalm, T.},
  booktitle = {Proceedings of the symposium on Data Visualisation 2002},
  interhash = {7d070baa654fc70cb8a0b1e373d90e2a},
  intrahash = {e5e72eed2d871523dc1100f060658a1c},
  isbn = {1-58113-536-X},
  location = {Barcelona, Spain},
  pages = {159--ff},
  publisher = {Eurographics Association},
  series = {VISSYM '02},
  title = {Visualization of bibliographic networks with a reshaped landscape metaphor},
  url = {http://portal.acm.org/citation.cfm?id=509740.509765},
  year = 2002
}

@inproceedings{1271658,
  abstract = {Bibliometric analysis is used as a measuring activity technique for basic research. There are many country level analyses of trends in scientific publications. These analyses give us an understanding of the macro-scale character of scientific activities. However, it is difficult to capture the qualitative evolution of scientific activities through them. In this regard, a meso-scale analysis of science activities, i.e., analysis of "research areas", is suitable for grasping qualitative changes in scientific activities. In this study, we develop a new method for mapping science at the research area level. Our method consists of two parts: constructing research areas from scientific publications and content analysis by experts. Research areas are explored through a co-citation analysis, and a map of science was generated to analyze how research areas relate to each other. This method contributes to endeavours to understand and track the changing nature of science.},
  address = {Washington, DC, USA},
  author = {SAKA, Ayaka and IGAMI, Masatsura},
  booktitle = {IV '07: Proceedings of the 11th International Conference Information Visualization},
  doi = {http://dx.doi.org/10.1109/IV.2007.77},
  interhash = {1586085e24335ab7d0f8f5530d32552d},
  intrahash = {a9168950512836c2155af1ed6dc99453},
  isbn = {0-7695-2900-3},
  pages = {453--458},
  publisher = {IEEE Computer Society},
  title = {Mapping Modern Science Using Co-citation Analysis},
  url = {http://portal.acm.org/citation.cfm?id=1270398.1271658},
  year = 2007
}