In this paper, we propose a new approach for recommender systems based on target tracking by Kalman filtering. We assume that users and their seen resources are vectors in the multidimensional space of the categories of the resources. Knowing this space, we propose an algorithm based on a Kalman filter to track users and to predict the best prediction of their future position in the recommendation space.
@article{arxiv.1012.3280,
title = {A new Recommender system based on target tracking: a Kalman Filter approach},
author = {Samuel Nowakowski and Cédric Bernier and Anne Boyer},
journal= {arXiv preprint arXiv:1012.3280},
year = {2010}
}