Accelerated unconstrained latent factorization of tensor model for Web service QoS estimation
Aiming at the problem that the Web service quality of service (QoS) estimation methods based on the Urinals non-negative latent factorization of tensor model (NLFT) depend heavily on non-negative initial random data and specially designed non-negative training schemes, which lead to low compatibility and scalability, an accelerated unconstrained la