期刊名称：International Journal of Computer and Information Technology
印刷版ISSN：2279-0764
出版年度：2018
卷号：7
期号：4
页码：190-197
出版社：International Journal of Computer and Information Technology
摘要：Recommendation systems are essential tools in ecommerce
web sites to help users find the items that might
interest them. Although much research has shown the best
algorithmic solutions, few studies rely on real products databases
and users’ perceptions. This study objective is, thus, to identify
what are Internet shoppers preferences for Top-N products
recommendation regarding the shopping steps. We have built
different algorithmic solutions and presented users in the context
of two different moments in the shopping process. Through a
survey, 202 users evaluated the presented items and the collected
data was compared using statistical and qualitative data analysis.
Our results have shown that users prefer different types of
recommendations in different shopping moments. This evidence
generates opportunity to further research and useful data for
web retailers.
关键词：recommendation; e;commerce; user perception;
content;based; collaborative;filtering
