摘要
我国政府管理模式正在从传统的行政管理模式向公共服务模式转变,电子政务个性化推荐是提升政府公共服务水平的有效手段。在国内外电子政务个性化推荐研究基础上,综合采用Apriori、FCC和协同过滤等多种推荐算法,通过用户数据挖掘,用户聚类,个性化推荐三个过程,有效缓解了数据矩阵的高维性和数据极端稀疏性,提高推荐精度,以"××中小企业网"为例,验证了该个性化推荐算法的实用性和有效性。
Chinese government management mode is changing irom the traditional administrative management mode to public service mode, and personalized recommendation of e-government is the effective measures to enhance the level of government public service. In this paper,based on personalized recommendation of e-government research, many kinds of recommendation algorithm, such as Apriori, FCC and collaborative filtering recommendation, are combined to reduce effectively the high dimensional and the extreme of data matrix, and to improve the recommendation accuracy, with three processes of data mining,clustering and user personalization recommendation. ＂ ×× small and medium-sized enterprise network＂ is used to verify the practicability and validity of the personalized recommendation algorithm.
出处
《信息技术》
2015年第1期69-72,76,共5页
Information Technology
基金
国家自然科学基金(71271104
70971056
71101065)
教育部人文社会科学研究青年基金项目(10YJC630242)
江苏省教育厅高校哲学社会科学项目(2012SJD630017)
关键词
电子政务
公共服务
个性化推荐
e-government
public service
personalized recommendation
