A Survey on Quantum Computing for Recommendation Systems

Recommendation systems play a key role in everyday life; they are used to suggest items that selected among many candidates usually belong huge datasets. The recommendations require good performance both terms of speed and the effectiveness provided suggestions. At same time, one most challenging approaches computer science is quantum computing. This computational paradigm can provide significant acceleration for resource-demanding time-consuming algorithms. It has become very popular recent years, thanks different tools available scientific technical communities. Since great relevance recommendation systems, researchers community have recently proposed improvements exploit better systems. paper gives an overview current state art literature, outlining methodologies techniques highlighting challenges arise from this new approach domain.