摘要
在网络和用户规模不断扩大的背景下,用户对网络感知的要求迅猛提升,为解决网络中人流密集、用户价值高的沿街商铺场景深度覆盖差问题,利用网络爬虫程序批量获取商铺的互联网数据,同时结合移动网络数据,将商铺信息与移动网络信息关联,运用大数据工具进行数据挖掘,对沿街商铺口碑场景进行精准覆盖评估与规划,改善了用户感知与口碑,提升了工作效率。
The network and the user is expanding in the background,users'requirements for network awareness are rapidly increasing.In order to solve the problem of poor depth coverage of shops along the street with dense traffic and high user value in the network,the Internet crawler program is used to obtain the Internet data of the store in batches.At the same time,combined with mobile network data,the store information is associated with the mobile network information,using the big data tools for data mining,accurate coverage assessment and planning for the street-storing word-of-mouth scenes,improving user perception and word of mouth,and improving work efficiency.
作者
苏大芹
刘燕
Su Daqin;Liu Yan(China Unicom Henan Branch,Zhengzhou 450008,China)
出处
《邮电设计技术》
2019年第2期85-89,共5页
Designing Techniques of Posts and Telecommunications
关键词
大数据分析
沿街商铺
互联网
覆盖评估
智能识别
深度覆盖
Big data analysis
Street shops
Internet
Coverage assessment
Intelligent identification
Deep coverage
