Study on E-commerce recommendation based on content analysis
Zhang Guangqian, Lei Caihua · 2011
By using content analysis, 101 journal articles about E-commerce recommendation between 2000 ∼ 2010 year have been statistically analyzed in the text, and the four categories of E-commerce recommendation framework include theoretical overviews, E-commerce recommendation technology, security system of E-commerce recommendation and the recommendation applications, which have been establishment. The text detects the research and development of E-commerce recommendation in the hot areas for nearly ten years. The research shows that the recommendation research are focused on algorithm, especially the collaboration filtering algorithms, but security system of E-commerce recommendation and the recommendation applications are the weak link, so through analyzing development trend of the recommendations can provide support for future study of E-commerce recommendation.