基于游客好奇心的旅游信息推荐系统

Tourist Information Recommendation System Based on Tourists’Curiosity

从庞大的旅游信息中筛选出针对游客兴趣的信息是当前旅游推荐系统有待解决的问题。针对以往兴趣推荐算法的缺陷,将游客好奇心作为参考特征,并将其转化为新颖度计算,利用Python语言开发了旅游信息推荐系统。该系统能够按照景点分类、游客信息自动计算出游客感兴趣的景点进行推荐。对比可知,相比三种主流的旅游信息推荐系统在推荐准确率、用户召回率和景点覆盖率方面表现较好,说明该系统具有一定的应用价值。为旅游推荐算法和系统的改进提供了参考。

Screening out the tourist interest information from the huge tourism information is a problem to be solved in the current tourism recommendation system.In view of the defects of previous interest recommendation algorithms,tourist curiosity is taken as a reference feature and transformed into novelty calculation.A tourism information recommendation system is developed by using Python.The system can automatically calculate the attractions that tourists are interested in and recommend them according to the classification of scenic spots and tourist information.Compared with the three mainstream tourism information recommendation systems,this system performs better in recommendation accuracy rate,user recall rate and scenic spot coverage rate,which indicates that the system has certain application value.This paper provides a reference for the improvement of tourism recommendation algorithm and system.