A demographic-based and expertise-enhanced collaborative filtering method for e-government service recommendation

作者：Zhang Shuai; Zhu Yuan^*; Wang Yan; Zhang Wenyu; Li Yong

来源：Journal of Computational Information Systems, 2014, 10(6): 2463-2480.

DOI：10.12733/jcis9795

• Demographic information
• Domain experts
• E-government services
• Service clustering
• Service recommendations

Recently collaborative filtering is a very popular recommendation technique to deal with service explosion in e-government area. The traditional collaborative filtering method concentrates on finding the rating similar users to act as reference users for the active user. However, as e-government may be related to many requirements and constraints, such as age, region and profession, etc., the citizen users in this area especially need more of the help and guidance from experts than just rating similar users. This paper presents a demographic-based and expertise-enhanced collaborative filtering method to solve the above problems in e-government service recommendation due to the specialty of government area. The involved experts here are domain experts identified from usage experience and social influence, which is skilled in a certain kind of e-government services gathered through clustering methods. In addition, because the laws and regulations in different places are diverse for different e-government services as well as citizens with different ages, the demographic information such as age, region and profession will be used to select similar users that are more preferable, personalized and trustable than other common users for recommendation reference.

• 出版日期2014
• 单位浙江大学