A novel quantum recommender system

Abstract Recommendation system is a kind of information filtering system, which plays an increasingly important role in the era of big data. In this work, we present a novel quantum recommender system, which can also be regarded as a quantum version of the matrix reconstruction algorithm. In order to obtain two factors in the quantum state form, a quantum version of the alternating least squares algorithm is designed. And based on the factor matrices, the reconstruction matrix of the original rating matrix is calculated. The complexity analysis shows that our quantum algorithm may achieve an exponential speedup relative to the classical counterpart under certain conditions.