Recommender systems use algorithms to provide users with product or service
recommendations. Recently, these systems have been using machine learning algorithms …

The ongoing rapid expansion of the Internet greatly increases the necessity of effective
recommender systems for filtering the abundant information. Extensive research for …

全面地总结推荐系统的研究现状, 旨在介绍网络推荐的算法思想, 帮助读者了解这个研究领域.
首先阐述了推荐系统研究的工业需求, 主要研究机构和成果发表的期刊会议; …

摘要互联网技术的迅猛发展把我们带进了信息爆炸的时代. 海量信息的同时呈现,
一方面使用户很难从中发现自己感兴趣的部分, 另一方面也使得大量少人问津的信息成为网络中 …

The industrial Internet of things (IIoT), a new computing mode in Industry 4.0, is deployed to
connect IoT devices and use communication technology to respond to control commands …

Recommender systems have been in existence everywhere with most of them using single
ratings in prediction. However, multi-criteria predictions have been proved to be more …

Among different hybrid recommendation techniques, network-based entity recommendation
methods, which utilize user or item relationship information, are beginning to attract …

Due to the explosion of available information on the Internet, the need for effective means of
accessing and processing them has become vital for everyone. Recommender systems …

Although Recommender Systems have been comprehensively analyzed in the past decade,
the study of social-based recommender systems just started. In this paper, aiming at …

Among collaborative recommendation approaches, methods based on nearest-neighbors
still enjoy a huge amount of popularity, due to their simplicity, their efficiency, and their ability …