Qingyi Hua

TL;DR: The recent hybrid CF-based recommendation techniques fusing social networks to solve data sparsity and high dimensionality are introduced and provide a novel point of view to improve the performance of RS, thereby presenting a useful resource in the state-of-the-art research result for future researchers.

TL;DR: A path planning method for UAV-assisted data collection which can plan an energy-efficient flight path and can obtain data collection path with lower energy consumption and smoother path trajectory, which is more suitable for actual flight.

TL;DR: A novel social matrix factorization-based recommendation method is proposed to improve the recommendation quality by fusing user’s social status and homophily and is evaluated using real-life datasets including the Epinions and Douban datasets.

TL;DR: This paper fuse personal cognition behavior, cognition relationships between users, and time decay factor for rated items into a unified probabilistic matrix factorization model and propose an enhanced social matrix factorizations approach for personalized recommendation using social interaction factors.

TL;DR: Wang et al. as mentioned in this paper used ensemble learning model to analyze and predict anomaly of the massive system logs based on the complete procedures of log processing, including log analysis, feature extraction, anomaly detection, prediction evaluation, and real-time reliability evaluation.