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利用内容分析法,对2000-2010年间国内期刊上101篇与电子商务推荐技术相关的学术性论文进行统计分析。建立以理论性综述、推荐技术研究、推荐系统安全性研究与应用研究四大类为基础的电子商务推荐分类框架,以此探析近10年电子商务推荐研究的热点领域及发展变化。研究结果表明,电子商务推荐研究的重点领域主要集中在算法研究方面,尤其是协同过滤算法的研究,而电子商务推荐系统的安全性及电子商务推荐的应用是目前电子商务推荐研究中最为薄弱的环节。通过对电子商务推荐发展趋势的描述,为未来电子商务推荐研究和应用提供研究支持。
Using content analysis method, statistical analysis was made on 101 academic papers related to e-commerce recommendation technology in domestic journals between 2000 and 2010. Established a four-category e-commerce recommendation classification framework based on theoretical review, recommendation technology research, and recommendation system security research and application research, to analyze the hot areas and development changes of e-commerce recommendation research in the past 10 years. The research results show that the focus areas of e-commerce recommendation research mainly focus on algorithm research, especially the research of collaborative filtering algorithms. The security of e-commerce recommendation system and the application of e-commerce recommendation are the weakest in e-commerce recommendation research. Link. Through the description of the development trend of e-commerce recommendation, research support for the e-commerce recommendation research and application will be provided.