摘要
在大数据信息技术的推动下,车货匹配平台迅速发展,市场竞争日趋激烈,同时市场对车货信息匹配精准度和效率有了更高要求。提高车货信息匹配的精准度不仅有助于车货匹配平台降低运营成本,提高业务效率,辅助业务决策,从而还可以实现更加有效地提高客户满意度。因此,文章通过对车货匹配现状进行分析,结合车货匹配平台的用户业务数据和行为数据,利用画像技术建立合理的画像标签体系,运用协同过滤推荐算法挖掘出具有不同业务类型的用户群体,以期为用户提供精准化个性服务。
With the promotion of big data information technology, the vehicle and cargo matching platform develops rapidly,and the market competition becomes increasingly fierce. At the same time, the market has higher requirements for the accuracy and efficiency of vehicle and cargo information matching.Improving the accuracy of vehicle and cargo information matching not only helps the vehicle and cargo matching platform to reduce operating costs, improve business efficiency and assist business decisions, but also can achieve more effective improvement of customer satisfaction. Therefore, by analyzing the status quo of vehicle and cargo matching and combining the user business data and behavior data of the vehicle and cargo matching platform, this paper uses portrait technology to establish a reasonable portrait labeling system, and uses collaborative filtering recommendation algorithm to mine out user groups with different business types, in order to provide accurate personalized services for users.
作者
李红莹
张志清
LI Hongying;ZHANG Zhiqing(Evergrande School of Management,Wuhan University of Science and Technology,Wuhan 430065,China;Service Science and Engineering Research Center,Wuhan University of Science and Technology,Wuhan 430065,China)
出处
《物流科技》
2021年第11期18-21,26,共5页
Logistics Sci-Tech
基金
湖北省教育厅人文社科重点项目“面向产教精准对接的智能化信息服务与长效机制研究”(20D019)。
关键词
画像技术
车货匹配
协同过滤
user portrait
vehicle-cargo matching
collabora-tive filtering