Tootfinder

eu_procurements: EU procurement contract networks (2008-2016)
A bipartite network of public EU procurement contracts, from 2008 to 2016, between issuing buyers (public institutions such as a ministry or city hall) and supplying winners (a private firm). Contracts are aggregated into annual snapshots, edges are annotated with contract value information. Nodes are annotated with location information, including country of origin.
This network has 839824 nodes and 4098711 edges.

🎉 perfSONAR turns 20! 🎉
What started with a single line of code in 2001 has grown into a worldwide network performance monitoring infrastructure, spanning all 7 continents with:
✅ 20 years of continuous operation
✅ 6 leading R&E networks driving its development
✅ over 2,000 registered instances deployed across 1,000 organizations
Learn more about perfSONAR’s journey and impact over the past 20 years:

perfSONAR Celebrates 20 Years of Simplifying Global Research Collaboration Through Standardized Network Measurement and Testing | GÉANT CONNECT Online
April 2, 2025 — The global research and education (R&E) community is celebrating a major milestone in high-performance networking and collaboration: the 20th anniversary of perfSONAR. Since April 2005, this powerful, open-source toolkit has enabled researchers and network operators to measure and troubleshoot performance across diverse network environments. perfSONAR’s reach has extended to all seven

Identifying Alzheimer's Disease Prediction Strategies of Convolutional Neural Network Classifiers using R2* Maps and Spectral Clustering
Christian Tinauer, Maximilian Sackl, Stefan Ropele, Christian Langkammer
https://arxiv.org/abs/2506.03890

Identifying Alzheimer's Disease Prediction Strategies of Convolutional Neural Network Classifiers using R2* Maps and Spectral Clustering
Deep learning models have shown strong performance in classifying Alzheimer's disease (AD) from R2* maps, but their decision-making remains opaque, raising concerns about interpretability. Previous studies suggest biases in model decisions, necessitating further analysis. This study uses Layer-wise Relevance Propagation (LRP) and spectral clustering to explore classifier decision strategies across preprocessing and training configurations using R2* maps. We trained a 3D convolutional neural net…

as_skitter: Skitter IP graph (2005)
An aggregate snapshot of the Internet Protocol (IP) graph, as measured by the traceroute tool on CAIDA's skitter infrastructure, in 2005.
This network has 1696415 nodes and 11095298 edges.
Tags: Technological, Communication, Unweighted
https://networks.skewed.de/net/as_s…

This https://arxiv.org/abs/2505.00393 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDB_…

S3AND: Efficient Subgraph Similarity Search Under Aggregated Neighbor Difference Semantics (Technical Report)
For the past decades, the \textit{subgraph similarity search} over a large-scale data graph has become increasingly important and crucial in many real-world applications, such as social network analysis, bioinformatics network analytics, knowledge graph discovery, and many others. While previous works on subgraph similarity search used various graph similarity metrics such as the graph isomorphism, graph edit distance, and so on, in this paper, we propose a novel problem, namely \textit{subgrap…

This https://arxiv.org/abs/2412.07901 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Homophily Within and Across Groups
Homophily-the tendency to connect with similar others-plays a central role in shaping network structure and function. It is often treated as a uniform, global parameter, independent from other structural features. Here, we propose a maximum-entropy framework that decomposes homophily into contributions within and across groups, with the stochastic block model emerging as a special case. Our exponential-family formulation, parameterized by group size, fits real-world social networks well and all…

This https://arxiv.org/abs/2505.06612 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSI_…

Burger: Robust Graph Denoising-augmentation Fusion and Multi-semantic Modeling in Social Recommendation
In the era of rapid development of social media, social recommendation systems as hybrid recommendation systems have been widely applied. Existing methods capture interest similarity between users to filter out interest-irrelevant relations in social networks that inevitably decrease recommendation accuracy, however, limited research has a focus on the mutual influence of semantic information between the social network and the user-item interaction network for further improving social recommend…

tree-of-life: Protein interactomes across the tree of life (2019)
Protein-protein iteraction networks ("interactome") for 1,840 species. An interactome captures all physical protein-protein interactions within one species, from direct biophysical protein-protein interactions to regulatory protein-DNA and metabolic interactions. .
This network has 562 nodes and 994 edges.
Tags: Biological, Protein interactions

Upcoming GÉANT infoshare - Part 2 🚀
🔹 Network eAcademy Infoshare
Hear about latest developments in the GÉANT #Network #eAcademy, what’s new across different tracks from Automation to Artificial Intelligence to Quantum Technologies and Optical Time and Frequency Networks (OTFN).
👥 Hoste…

Infoshare: Network eAcademy
The Network eAcademy is a service created to help and support organisations in human capital development in Network-development-related domains. Among the activities the Network eAcademy team is developing, we can find the publication of contents around orchestration, automation and virtualisation, such as architecture analysis, terminology or a Maturity Model, and training programmes “from the community for the community”. The training programmes are continuously developed, with...

tree-of-life: Protein interactomes across the tree of life (2019)
Protein-protein iteraction networks ("interactome") for 1,840 species. An interactome captures all physical protein-protein interactions within one species, from direct biophysical protein-protein interactions to regulatory protein-DNA and metabolic interactions. .
This network has 562 nodes and 994 edges.
Tags: Biological, Protein interactions