Personalized Service Recommendation for Collaborative Tagging Systems with Social Relations and Temporal Influences
Zigui Jiang, Ao Zhou, Shangguang Wang, Qibo Sun, Rongheng Lin, Fangchun Yang · 2016
Personalized service recommendation becomes increasingly essential because of the growing number of services. To enhance the performance of personalized service recommendation in collaborative tagging systems, not only tag information but also time and social relations information should be considered. In this paper, we propose a hybrid method aiming at taking advantage of tag, time and users' social relations information for a preferable service recommendation. We first improve a simple tag-based recommendation method by a time-decay function. Then we develop a temporal social-based recommendation method which analyzes user familiarity and user preference similarity between friends. Based on these two steps we integrate them as a temporal tag-and social-based (TTS) recommendation algorithm. Experiment results indicate that our method outperforms general tag-based and social-based recommendation methods.