Frontier Dynamics of Big Data Recommendation Algorithm at Home and Abroad
Chen Jun1,2, Xie Weihong1,2, Chen Yangsen1
1.School of Management,Guangdong University of Technology,Guangzhou 510520,China 2.Big data Strategy Research Institute of Guangdong University of Technology,Guangzhou 510520,China
摘要大数据时代下,信息过载问题日益突出,使得大数据推荐算法研究显得尤为重要。 本文基于Web of Science和中国知网的大数据推荐算法期刊文献数据,运用文献计量、共词分析和社会网络方法,从高频关键词共现、关键词主题演进、研究动态等方面对大数据推荐算法领域的总体情况进行量化比较研究。结果显示,国外大数据推荐算法在理论和应用的研究上都领先于国内,特别是在应用上的广度和深度是国内大数据推荐算法需要加强研究的方向。大数据推荐算法朝着个性化教育、个性化医疗、个性化社会网络服务等应用领域发展。本文对促进中国大数据推荐算法理论的纵深研究、深层次的应用研究以及向着国际化发展具有一定的指导意义。
Abstract：In the age of big data,the problem of information overload has become increasingly prominent,then the research on big data recommendation algorithm has become increasingly important.This paper takes the articles of big data recommendation algorithm from Web of Science and CNKI as data sources,and uses the method of bibliometrics,co-word analysis and SNA to do quantitative comparative analysis from co-word of high frequency keywords,the evolution of keywords and dynamics research.The results show that the abroad research on the theory and application of big data recommendation algorithm are matured than the domestic.Especially we should strengthen the study of the application's breadth and depth.Big data recommendation algorithm develops into the trend of individualized education,personalized medical care,personalized social network service and other applications.This paper has a certain guiding significance to promote the deep research of the theory of big data recommendation algorithm,the deep application research and the development of internationalization.
陈军, 谢卫红, 陈扬森. 国内外大数据推荐算法领域前沿动态研究[J]. 中国科技论坛, 2018(1): 173-181.
Chen Jun, Xie Weihong, Chen Yangsen. Frontier Dynamics of Big Data Recommendation Algorithm at Home and Abroad. , 2018(1): 173-181.
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