Pajek -- analysis and visualization of large networks Pajek (spider, in Slovene) is a program package, for Windows (32 bit), for analysis and visualization of large networks (having thousands of vertices). It is freely available, for noncommercial use, at its home page:

References in zbMATH (referenced in 55 articles , 1 standard article )

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  1. Carvalho, Filipa D.; Almeida, Maria Teresa: The triangle $k$-club problem (2017)
  2. Arrigo, Francesca; Benzi, Michele; Fenu, Caterina: Computation of generalized matrix functions (2016)
  3. Murtagh, Fionn; Kurtz, Michael J.: The classification society’s bibliography over four decades: history and content analysis (2016)
  4. Reichel, Lothar; Spalević, Miodrag M.; Tang, Tunan: Generalized averaged Gauss quadrature rules for the approximation of matrix functionals (2016)
  5. Veremyev, Alexander; Prokopyev, Oleg A.; Butenko, Sergiy; Pasiliao, Eduardo L.: Exact MIP-based approaches for finding maximum quasi-cliques and dense subgraphs (2016)
  6. Cerinšek, Monika; Batagelj, Vladimir: Network analysis of Zentralblatt MATH data (2015)
  7. Estrada, Ernesto; Arrigo, Francesca: Predicting triadic closure in networks using communicability distance functions (2015)
  8. Fahimnia, Behnam; Tang, Christopher S.; Davarzani, Hoda; Sarkis, Joseph: Quantitative models for managing supply chain risks: a review (2015)
  9. Kajdanowicz, Tomasz: Relational classification using random walks in graphs (2015) ioport
  10. Mingers, John; Leydesdorff, Loet: A review of theory and practice in scientometrics (2015)
  11. Wiesberg, Stefan; Reinelt, Gerhard: Evaluating the quality of image matrices in blockmodeling (2015)
  12. Cafieri, Sonia; Costa, Alberto; Hansen, Pierre: Reformulation of a model for hierarchical divisive graph modularity maximization (2014)
  13. Costa, Alberto; Hansen, Pierre: A locally optimal hierarchical divisive heuristic for bipartite modularity maximization (2014)
  14. Kulinich, A.A.: Software systems for situation analysis and decision support on the basis of cognitive maps: approaches and methods (2014)
  15. Pajouh, Foad Mahdavi; Miao, Zhuqi; Balasundaram, Balabhaskar: A branch-and-bound approach for maximum quasi-cliques (2014)
  16. Ribeiro, Pedro; Silva, Fernando: G-Tries: a data structure for storing and finding subgraphs (2014)
  17. Veremyev, Alexander; Prokopyev, Oleg A.; Boginski, Vladimir; Pasiliao, Eduardo L.: Finding maximum subgraphs with relatively large vertex connectivity (2014)
  18. Hu, Jinyu; Gao, Zhiwei; Pan, Weisen: Multiangle social network recommendation algorithms and similarity network evaluation (2013)
  19. Malliaros, Fragkiskos D.; Vazirgiannis, Michalis: Clustering and community detection in directed networks: a survey (2013)
  20. Ma, Yu-Xin; Xu, Jia-Yi; Peng, Di-Chao; Zhang, Ting; Jin, Cheng-Zhe; Qu, Hua-Min; Chen, Wei; Peng, Qun-Sheng: A visual analysis approach for community detection of multi-context mobile social networks (2013) ioport

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