Bibliography

CDlib was developed for research purposes. Here you can find the complete list of papers that contributed to the algorithms and methods it exposes.

Algorithms

Evaluation measures

Researches using CDlib

So far it has been used to support the following research activities:

  • Hubert, M. Master Thesis. (2020) Crawling and Analysing code review networks on industry and open source data
  • Pister, A., Buono, P., Fekete, J. D., Plaisant, C., & Valdivia, P. (2020). Integrating Prior Knowledge in Mixed Initiative Social Network Clustering. arXiv preprint arXiv:2005.02972.
  • Mohammadmosaferi, K. K., & Naderi, H. (2020). Evolution of communities in dynamic social networks: An efficient map-based approach. Expert Systems with Applications, 147, 113221.
  • Cazabet, Remy, Souaad Boudebza, and Giulio Rossetti. “Evaluating community detection algorithms for progressively evolving graphs.” arXiv preprint arXiv:2007.08635 (2020).
  • Citraro, Salvatore, and Giulio Rossetti. “Identifying and exploiting homogeneous communities in labeled networks.” Applied Network Science 5.1 (2020): 1-20.
  • Citraro, Salvatore, and Giulio Rossetti. “Eva: Attribute-Aware Network Segmentation.” International Conference on Complex Networks and Their Applications. Springer, Cham, 2019.
  • Rossetti, Giulio. “ANGEL: efficient, and effective, node-centric community discovery in static and dynamic networks.” Applied Network Science 5.1 (2020): 1-23.
  • Jaiswal, Rajesh, and Sheela Ramanna. “Detecting Overlapping Communities Using Distributed Neighbourhood Threshold in Social Networks.” International Joint Conference on Rough Sets. Springer, Cham, 2020.
  • Rossetti, Giulio. “Exorcising the Demon: Angel, Efficient Node-Centric Community Discovery.” International Conference on Complex Networks and Their Applications. Springer, Cham, 2019.