The SmartData@PoliTO center focuses on Big Data technologies, Data Science and Machine Learning approaches.
We blend interdisciplinary people and competences from different domains to provide cross-domain solutions to the widest spectrum of knowledge discovery challenges, by leveraging advanced expertise in data science, from data management, to data modeling, analytics, and engineering.
We are a well-recognized center where experts in methodologies and domain experts from various disciplines work in a single space, facing both theoretical problems and helping companies toward applications.
Presenter: Andrea CavalloMonday, December 5th, 2022 17:00Location: SmartData@Covivio Graph Neural Networks (GNNs) achieve state-of-the-art performance on several tasks on graph-structured data. Their success is related to their capability to generate embeddings that model the entire neighborhood of a node, instead of just the node itself. This approach is very effective on homophilous graphs, i.e. graphs where same-type nodes tend to […]
This webpage contains additional material on the paper: “Where did my packet go? Real-time prediction of losses in networks” Currently under revision The data You can find the dataset on this link: RTP traffic losses data where the column “lossOrNot” is the target variable, the column “num_packet_loss” is the number of losses in that time […]
In this webpage, you can find the dataset we used in the paper: “A First Look at Starlink Performance” François Michel, Martino Trevisan, Danilo Giordano, Olivier Bonaventure. To Appear on the 2021 ACM Internet Measurement Conference. Summary With new Low Earth Orbit satellite constellations such as Starlink, satellite-based Internet access is becoming an alternative to […]
This repository contains data and information regarding the papers: L. Vassio, M. Garetto, C. Chiasserini, and E. Leonardi. Temporal Dynamics of Posts and User Engagement of Influencers on Facebook and Instagram. 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2021. DOI: 10.1145/3487351.3488340 L. Vassio, M. Garetto, C. Chiasserini, and E. […]