@inproceedings{ahmed2007visualisation,
  abstract = {In this paper, we present a case study for the visualisation and analysis of large and complex temporal multivariate networks derived from the Internet movie database (IMDB). Our approach is to integrate network analysis methods with visualisation in order to address scalability and complexity issues. In particular, we defined new analysis methods such as (p,q)-core and 4-ring to identify important dense subgraphs and short cycles from the huge bipartite graphs. We applied island analysis for a specific time slice in order to identify important and meaningful subgraphs. Further, a temporal Kevin Bacon graph and a temporal two mode network are extracted in order to provide insight and knowledge on the evolution.},
  author = {Ahmed, Adel and Batagelj, Vladimir and Fu, Xiaoyan and Hong, Seok-Hee and Merrick, Damian and Mrvar, Andrej},
  booktitle = {Visualization, 2007. APVIS '07. 2007 6th International Asia-Pacific Symposium on},
  doi = {10.1109/APVIS.2007.329304},
  interhash = {98c887b94e1826332d7739e3af78265e},
  intrahash = {4ce8ac41630e50a8447bd969ec1219da},
  month = {feb.},
  pages = {17 -24},
  title = {Visualisation and analysis of the internet movie database},
  url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4126213&tag=1},
  year = 2007
}

@incollection{batagelj1999partitioning,
  abstract = {The structure of large graphs can be revealed by partitioning graphs to smaller parts, which are easier to handle. In the paper we propose the use of core decomposition as an efficient approach for partitioning large graphs. On the selected subgraphs, computationally more intensive, clustering and blockmodeling can be used to analyze their internal structure. The approach is illustrated by an analysis of Snyder & Kick’s world trade graph.},
  address = {Berlin / Heidelberg},
  affiliation = {FMF, Department of Mathematics, and IMFM Department of Theoretical Computer Science University of Ljubljana Jadranska 19 1000 Ljubljana Slovenia},
  author = {Batagelj, Vladimir and Mrvar, Andrej and Zaveršnik, Matjaž},
  booktitle = {Graph Drawing},
  doi = {10.1007/3-540-46648-7_9},
  editor = {Kratochvíyl, Jan},
  interhash = {223ade3dd692bb262a6398e1442b4dfd},
  intrahash = {2e005638761fc15757dd18113783aa97},
  isbn = {978-3-540-66904-3},
  keyword = {Computer Science},
  pages = {90-97},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {Partitioning Approach to Visualization of Large Graphs},
  url = {http://dx.doi.org/10.1007/3-540-46648-7_9},
  volume = 1731,
  year = 1999
}

@book{nooy2005exploratory,
  asin = {0521602629},
  author = {de Nooy, Wouter and Mrvar, Andrej and Batagelj, Vladimir},
  dewey = {300.285},
  ean = {9780521602624},
  edition = {illustrated edition},
  interhash = {f482ff433e1826b278a27c5a7474f37e},
  intrahash = {fa414ff6ed7eb359bf598ac46fc38154},
  isbn = {0521602629},
  publisher = {Cambridge University Press},
  title = {Exploratory Social Network Analysis with Pajek (Structural Analysis in the Social Sciences)},
  url = {http://www.amazon.com/Exploratory-Network-Analysis-Structural-Sciences/dp/0521602629},
  year = 2005
}

@book{nooy2005pajek,
  address = {New York, NY, USA},
  asin = {0521602629},
  author = {de Nooy, Wouter and Mrvar, Andrej and Batagelj, Vladimir},
  dewey = {300.285},
  ean = {9780521602624},
  interhash = {deb32e4829c9c2b16857a7ced06b89eb},
  intrahash = {114a68aea38d947757b10531d599e6b8},
  isbn = {0521602629},
  number = 27,
  publisher = {Cambridge University Press},
  series = {Structural Analysis in the Social Sciences},
  title = {Exploratory Social Network Analysis with Pajek},
  url = {http://www.amazon.com/Exploratory-Network-Analysis-Structural-Sciences/dp/0521602629%3FSubscriptionId%3D192BW6DQ43CK9FN0ZGG2%26tag%3Dws%26linkCode%3Dxm2%26camp%3D2025%26creative%3D165953%26creativeASIN%3D0521602629},
  year = 2005
}