Yunni Xia

An Efficient Second-Order Approach to Factorize Sparse Matrices in Recommender Systems

2015 · IEEE Transactions on Industrial Informatics

Recommender systems are an important kind of learning systems, which can be achieved by latent-factor (LF)-based collaborative filtering (CF) with high efficiency and scalability. LF-based CF models rely on an optimization process with respect to …

Generating Highly Accurate Predictions for Missing QoS Data via Aggregating Nonnegative Latent Factor Models

2015 · IEEE Transactions on Neural Networks and Learning Systems

Automatic Web-service selection is an important research topic in the domain of service computing. During this process, reliable predictions for quality of service (QoS) based on historical service invocations are vital to users. This work …

A Nonnegative Latent Factor Model for Large-Scale Sparse Matrices in Recommender Systems via Alternating Direction Method

2015 · IEEE Transactions on Neural Networks and Learning Systems

Nonnegative matrix factorization (NMF)-based models possess fine representativeness of a target matrix, which is critically important in collaborative filtering (CF)-based recommender systems. However, current NMF-based CF recommenders suffer from the problem of high computational and …