语义推荐算法研究综述  

Survey of Semantics-Based Recommendation Algorithms

作　　者：黄震华[1] 张佳雯[1] 张波[2] 喻剑[1] 向阳[1] 黄德双[1] 

机构地区：[1]同济大学电子与信息工程学院,上海201804 [2]上海师范大学信息与机电工程学院,上海200234

出　　处：《电子学报》2016年第9期2262-2275,共14页Acta Electronica Sinica

基　　金：国家自然科学基金(No.61272268);上海市青年科技启明星计划(No.15QA1403900);教育部新世纪优秀人才支持计划(No.NCET-12-0413);国家973课题(No.2014CB340404);霍英东基金应用类课题(No.142002);同济大学中央高校基本科研业务费专项资金

摘　　要：近年来,语义推荐技术已成为信息服务领域的一个研究热点和重点.与传统的推荐算法相比,语义推荐算法在实时性、鲁棒性和推荐质量等方面具有显著的优势.针对语义推荐算法的国内外研究现状、进展,从四个角度进行归纳和总结,即基于语义的内容推荐算法、基于语义的协同过滤推荐算法、基于语义的混合推荐算法以及基于语义的社会化推荐算法,旨在尽可能全面地对语义推荐算法进行细致的介绍与分析,为相关研究人员提供有价值的学术参考.最后,立足于研究现状的分析与把握,对当前语义推荐算法所面临的挑战与发展趋势进行了展望.Semantics-based recommendation technology has recently received a lot of attention in information services community. Compared with traditional recommendation algorithms,semantics-based recommendation algorithms have the marked advantages in the aspects of real-timing,robustness and recommendation quality. From the status and progress of domestic and foreign research,we summarize the following four aspects： semantics-based content recommendation algorithms,semantics-based collaborative filtering recommendation algorithms,semantics-based hybrid recommendation algorithms,and semantics-based social recommendation algorithms. And this paper is expected to provide a worthwhile reference for relevant researchers by detailedly analyzing semantics-based recommendation algorithms. Finally,we showreaders the challenges and future research directions in this field.

关 键 词：语义 推荐算法 内容推荐 协同过滤推荐 混合推荐 社会化推荐 

分 类 号：TN911.23[电子电信—通信与信息系统]