TGLib: An Open-Source Library for Temporal Graph Analysis

We initiate an open-source library for the efficient analysis of temporal graphs. We consider one of the standard models of dynamic networks in which each edge has a discrete timestamp and transition time. Recently there has been a massive interest in analyzing such temporal graphs. Common computational data mining and analysis tasks include the computation of temporal distances, centrality measures, and network statistics like topological overlap, burstiness, or temporal diameter. To fulfill the increasing demand for efficient and easy-to-use imple-mentations of temporal graph algorithms, we introduce the open-source library Tglib,which integrates efficient data structures and algorithms for temporal graph analysis. Tglibis highly efficient and versatile, providing simple and convenient C++ and Python interfaces, targeting computer scientists, practitioners, students, and the (temporal) network research community.

  • Published in:
    International Conference on Data Mining Workshops
  • Type:
  • Authors:
    Oettershagen, Lutz; Mutzel, Petra
  • Year:

Citation information

Oettershagen, Lutz; Mutzel, Petra: TGLib: An Open-Source Library for Temporal Graph Analysis, International Conference on Data Mining Workshops, 2022,, Oettershagen.Mutzel.2022a,

Associated Lamarr Researchers

lamarr institute person Mutzel Petra - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Petra Mutzel

Principal Investigator Hybrid ML to the profile