TGLib: An Open-Source Library for Temporal Graph Analysis
Lutz Oettershagen, Petra Mutzel

TL;DR
TGLib is an open-source library designed for efficient analysis of temporal graphs, offering data structures and algorithms with user-friendly interfaces for researchers and practitioners.
Contribution
It introduces a versatile, efficient, and easy-to-use open-source library for temporal graph analysis with implementations in C++ and Python.
Findings
High efficiency in temporal graph computations
Versatile interfaces for diverse user needs
Supports standard temporal network analysis tasks
Abstract
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 implementations of temporal graph algorithms, we introduce the open-source library TGLib, which integrates efficient data structures and algorithms for temporal graph analysis. TGLib is highly efficient and versatile, providing simple and convenient C++ and Python interfaces, targeting computer scientists, practitioners, students, and the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComplex Network Analysis Techniques · Opportunistic and Delay-Tolerant Networks · Data Visualization and Analytics
