摘要
针对大型商场传统导航和搜索效率低的问题,设计了一种导购策略,采用改进后的A*算法实现最优路径的规划,根据混合交叉推荐技术进行数据采集与数据推荐,加强算法对复杂室内地图环境的适应性,提高推荐效率。构建了基于微信小程序的大型商场智能导购系统进行验证,在店铺搜索和推荐逻辑模型下,搜索效率提升了近50%,并解决了室内导航以及信息个性化推荐问题。
In order to solve the low efficiency of traditional navigation and search in large shopping malls,a shopping guide strategy is designed,which uses improved A-Star algorithm to realize the optimal path planning,and according to the hybrid cross recommendation technology,carries out the data collection and data recommendation to strengthen the adaptability of the algorithm to the complex indoor map environment and improve the recommendation efficiency.An intelligent shopping guide system for large shopping malls based on WeChat mini program is built to make the verification.With the logic model of shop search and recommendation,the search efficiency has been improved by nearly 50%,and the problems of indoor navigation and personalized information recommendation are solved.
作者
叶小艳
邓可儿
钟彬胜
梁梓滢
卓圳豪
钟华钧
Ye Xiaoyan;Deng Ke'er;Zhong Binsheng;Liang Ziying;Zhuo Zhenhao;Zhong Huajun(Department of network technology,Guangzhou Institute of software,Guangzhou,Guangdong 510990,China)
出处
《计算机时代》
2021年第8期17-20,23,共5页
Computer Era
基金
广东省科技创新战略专项资金(“攀登计划”专项资金)项目(pdjh2020a0862)。
关键词
A^(*)算法
导购策略
导航
推荐
搜索
A-Star algorithm
shopping guide strategy
navigation
recommendation
search
