基于Apriori改进算法及行为分析的旅游景区推荐系统

Research on Recommendation System of Scenic Spots Based on Improved Apriori Algorithm and Behavior Analysis

当前,推荐系统生成景区推荐列表速度慢且推荐的景区范围小,提出了基于Apriori改进算法及行为分析的旅游景区推荐系统。采用B/S架构设计系统总体架构;设计用户行为序列生成流程,构建用户行为特征文件;将用户行为划分为3个层次;采用Apriori改进算法计算用户行为项目最低支持数,生成用户推荐旅游景区推荐列表。系统推荐测评结果表明:设计系统生成的景区推荐列表速度快且推荐景区范围广。

At present,the speed of scenic spot recommendation list generated by the recommendation system is slow and the recommended scenic spot range is small.Therefore,a recommendation system of scenic spots based on improved Apriori algorithm and behavior analysis is proposed.B/S architecture is adopted to design the overall system architecture;The user behavior sequence generation process is designed to construct the user behavior characteristic file;The user behaviors are divided into three levels;The improved Apriori algorithm is used to calculate the minimum support number of user behavior items and generate the recommended list of user recommendation scenic spots.The system recommendation evaluation results show that the speed of the scenic spot recommendation list generated by the design system is fast,which has a wide range of recommended scenic spots.