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Similarity measures on graphs and novel methods for collaborative filtering

par Devooght, Robin
Président du jury Vansummeren, Stijn
Promoteur Bersini, Hugues
Co-Promoteur Saerens, Marco
Publication Non publié, 2017-06-28

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Résumé :

This work tackles different aspects of how to predict users' interest and behavior with social networks and recommender systems. On social network, we worked on the definition of similarity measure and on how to use them to predict characteristics of the nodes of a network. On recommender systems, we focused on improving collaborative filtering methods, which are a family of recommender systems based on the modelling of user-item interactions. We developed solutions to update models in real-time based on new observations, to exploit the order in which interactions happened to improve recommendation, and to speed up recommendations through the clustering of items.