计算机工程与应用2020，Vol.56Issue(1)：1-10,10.DOI:10.3778/j.issn.1002-8331.1907-0378
社会化推荐系统综述
Review of Social Recommender Systems
摘要
Abstract
Recommender systems can help netizens find target information from a large number of complex information, and can effectively improve netizens’information retrieval ability, However, there are problems in data sparsity, cold-start and system performance in recommender systems. In order to solve these problems, some scholars proposed to apply social relations to the recommender systems, this method is an important way to improve the accuracy of recommendation, and has made important progress in many years of scientific research practice. Therefore, this research direction has increasingly become a field of concern for many scholars, and relevant research in this field is becoming more and more active. By sorting out the concept of social recommender systems and comparing with traditional recommender systems, the research status of social recommender systems is reviewed, hoping to find out new rules and seek new breakthroughs from the current research status, the prospects for future development of the social recommender systems are also discussed, in order to be helpful to the later researchers.关键词
推荐系统/社会化推荐/协同过滤/矩阵分解/社交媒体Key words
recommender systems/social recommendation/collaborative filtering/matrix factorization/social media分类
信息技术与安全科学引用本文复制引用
张岐山,翁丽娟..社会化推荐系统综述[J].计算机工程与应用,2020,56(1):1-10,10.基金项目
国家自然科学基金(No.61300104) （No.61300104）
福建省自然科学基金(No.2018J01791). （No.2018J01791）
