186 citations · 186 across the 5 of their papers we have counts for
7 papers
Exploring and mining attributed sequences of interactions
Tiphaine Viard, Henry Soldano, Guillaume Santini
We are faced with data comprised of entities interacting over time: this can be individuals meeting, customers buying products, machines exchanging packets on the IP network, among…
Classifying Wikipedia in a fine-grained hierarchy: what graphs can contribute
Tiphaine Viard, Thomas McLachlan, Hamidreza Ghader +1
Wikipedia is a huge opportunity for machine learning, being the largest semi-structured base of knowledge available. Because of this, many works examine its contents, and focus on…
Introducing multilayer stream graphs and layer centralities
Pimprenelle Parmentier, Tiphaine Viard, Benjamin Renoust +1
Graphs are commonly used in mathematics to represent some relationships between items. However, as simple objects, they sometimes fail to capture all relevant aspects of real-world…
Degree-based Outlier Detection within IP Traffic Modelled as a Link Stream
Audrey Wilmet, Tiphaine Viard, Matthieu Latapy +1
This paper aims at precisely detecting and identifying anomalous events in IP traffic. To this end, we adopt the link stream formalism which properly captures temporal and structur…
Movie rating prediction using content-based and link stream features
Tiphaine Viard, Raphaël Fournier-S'niehotta
While graph-based collaborative filtering recommender systems have been introduced several years ago, there are still several shortcomings to deal with, the temporal information be…
Stream Graphs and Link Streams for the Modeling of Interactions over Time
Matthieu Latapy, Tiphaine Viard, Clémence Magnien
Graph theory provides a language for studying the structure of relations, and it is often used to study interactions over time too. However, it poorly captures the both temporal an…