Graph-Based Recommendation System [article]

Kaige Yang, Laura Toni
2018 arXiv   pre-print
In this work, we study recommendation systems modelled as contextual multi-armed bandit (MAB) problems. We propose a graph-based recommendation system that learns and exploits the geometry of the user space to create meaningful clusters in the user domain. This reduces the dimensionality of the recommendation problem while preserving the accuracy of MAB. We then study the effect of graph sparsity and clusters size on the MAB performance and provide exhaustive simulation results both in
more » ... and in real-case datasets. Simulation results show improvements with respect to state-of-the-art MAB algorithms.
arXiv:1808.00004v1 fatcat:mvkl2rumrnglteraa7fxul3knm