基于社交网络的餐厅群体推荐模型及系统设计

Restaurant Group Recommendation Model and System Design Based on Social Network

在“互联网+”时代,消费者外出就餐时更多的倾向于通过美食类网站或者APP选择餐厅。但在群体外出就餐时如何高效、迅速地找到大部分人满意的餐厅给现有的餐厅推荐系统带来了新的挑战。文章从社交网络的角度,在分析餐厅群体就餐信息的基础上,构建了基于协同过滤算法的餐厅推荐模型,在此基础上提出了餐厅群体推荐系统设计方案。融合社交网络的餐厅群体推荐算法显著提高了群体推荐的效率,基于此设计的系统实现了推荐餐厅排序、就餐攻略分享、就餐体验评价等功能。

In the "Internet Plus" era, consumers tend to choose restaurants through gourmet websites or APP when they eat out. However, how to efficiently and quickly find restaurants that most people are satisfied with when groups go out to eat has brought new challenges to the existing restaurant recommendation system. From the point of view of social network, based on the analysis of restaurant group dining information, this paper constructs a restaurant recommendation model on the basis of collaborative filtering algorithm, and puts forward the design scheme of restaurant group recommendation system. The restaurant group recommendation algorithm based on social network significantly improves the efficiency of group recommendation. The system based on this design realizes the functions of recommended restaurant ranking, dining strategy sharing, dining experience evaluation and so on.