Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Recherche

Afficher tous les résultats pour

Accueil

Personne

Volodymyr Miz

Cette personne a quitté l’EPFL

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (5)

Page 1 sur 1

Dynamic pattern recognition in large-scale graphs with applications to social networks

Volodymyr Miz

A graph is a versatile data structure facilitating representation of interactions among objects in various complex systems. Very often these objects have attributes whose measurements change over time, reflecting the dynamics of the system. This general da ...

EPFL2020

A Graph-structured Dataset for Wikipedia Research

Pierre Vandergheynst, Nicolas Aspert, Volodymyr Miz, Benjamin Ricaud

Wikipedia is a rich and invaluable source of information. Its central place on the Web makes it a particularly interesting object of study for scientists. Researchers from different domains used various complex datasets related to Wikipedia to study langua ...

ACM2019

Anomaly detection in the dynamics of web and social networks

Pierre Vandergheynst, Benjamin Ricaud, Kirell Maël Benzi, Volodymyr Miz

In this work, we propose a new, fast and scalable method for anomaly detection in large time-evolving graphs. It may be a static graph with dynamic node attributes (e.g. time-series), or a graph evolving in time, such as a temporal network. We define an an ...

2019

What is Trending on Wikipedia? Capturing Trends and Language Biases Across Wikipedia Editions

Pierre Vandergheynst, Benjamin Ricaud, Nicolas Aspert, Volodymyr Miz

In this work, we propose an automatic evaluation and comparison of the browsing behavior of Wikipedia readers that can be applied to any language editions of Wikipedia. As an example, we focus on English, French, and Russian languages during the last four ...

ACM2020

Spikyball Sampling: Exploring Large Networks via an Inhomogeneous Filtered Diffusion

Benjamin Ricaud, Nicolas Aspert, Volodymyr Miz

Studying real-world networks such as social networks or web networks is a challenge. These networks often combine a complex, highly connected structure together with a large size. We propose a new approach for large scale networks that is able to automatic ...

2020