基于情境大数据的移动网购行为执行意向预测模型  

Prediction models on execution intention of mobile online shopping behaviors based on situational big data

作　　者：万年红[1] 王雪蓉[1] Wan Nianhong;Wang Xuerong(Digital Engineering School,Zhejiang Dongfang Polytechnic, Wenzhou, Zhejiang 325000, China)

机构地区：[1]浙江东方职业技术学院数字工程学院,浙江温州325000

出　　处：《计算机时代》2019年第4期26-29,共4页Computer Era

基　　金：2018年温州市哲学社会科学规划课题(18wsk292)

摘　　要：为了科学地对高度复杂、难控的移动网络环境下网购行为执行意向进行预测,首先采用基于数理统计函数、基于网格计算的函数、基于大数据定性划分函数提出移动网购行为执行意向的情境大数据挖掘方法;其次归纳基于情境大数据的移动网购行为执行意向演化动力机制,并设计基于情境大数据的移动网购行为执行意向预测算法和模型,进行趋势、结构、综合预测的结果分析;最后,进行应用实验。性能分析结果表明,该模型具有一定的实用价值。To predict scientifically execution intention of online shopping behaviors under the environment of highly complex and hard-to-control Mobile Internet, firstly, situational big data mining methods of execution intention of mobile online shopping behaviors were put forward by adopting functions based on mathematical statistics, functions based on grid computing and qualitative partition function based on big data;Secondly, dynamic mechanisms on execution intention evolution of mobile online shopping behaviors based on situational big data were summarized, and prediction algorithms and models on execution intention of mobile online shopping behaviors based on situational big data were designed, and result analysis of trend, structure and comprehensive prediction was carried out;Finally, application experiments were carried out. Results of performance analysis show that the model has certain practical value.

关 键 词：情境大数据 移动网购 网购行为 执行意向 预测 

分 类 号：TP387[自动化与计算机技术—计算机系统结构]