Magnet is a joint team between the University of Lille within the CRIStAL and Inria Lille Nord Europe. The Magnet project aims to design new machine learning based methods geared towards mining information networks. Information networks are large collections of interconnected data and documents like citation networks and blog networks among others. For this, we will define new structured prediction methods for (networks of) texts based on machine learning algorithms in graphs. Such algorithms include node classification, link prediction, clustering and probabilistic modeling of graphs. Envisioned applications include browsing, monitoring and recommender systems, and more broadly information extraction in information networks. Application domains cover social networks for cultural data and e-commerce, and biomedical informatics.
Specifically, our main objectives are :
Each item will also be studied in contexts where little (if any) supervision is available. Therefore, semi-supervised and unsupervised learning will be considered throughout the project.
Semi-supervised graph clustering and information diffusion
Graph-based Learning for Multi-lingual and Multi-domain Dependency Parsing
Machine Learning Algorithms on Signed Graphs for Link Ranking and Classification
Adaptative Graph Learning with Applications to Natural Language Processing
Recommandation au sein de réseaux d'informations
Hypernode Graphs For Learning From Binary Relations Between Sets of Objects 2015-01-23