摘要
现实社会中每个人的行为特征具有典型的个性化属性,通过面向社会大众行为的普适性模型去推理个体行为的特征具有一定的困难和误差。在当前移动互联网信息化的大背景下,大数据为我们提供了丰富的数据集。文中探讨了在大数据平台对移动互联网用户社交网络关系的特征采集基础上,通过LSTM和Apriori理论的算法模型构建,实现时空位置轨迹下的网络行为分析和推理。
In the real world,every human’s behavior characteristics possess typical personalized attributes. There are difficulties and errors in reasoning individual behavior characteristics just through the general applicable models facing the public behaviors. In the current mobile internet information age,big data provides us with a rich set of data. The essay explores how to make use of the characteristics collection of the mobile internet user’s social network relationship through the big data platform,as well as the LSTM and the Apriori mathematical theory model to realize the analysis and inference of online behaviors under the time-space trajectory.
作者
徐运海
李道远
黄昌金
王庆友
XU Yun-hai;LI Dao-yuan;HUANG Jin-chang;WANG Qing-you(Guangzhou Intelligence Communications Technology Co.,Ltd.Guangzhou 510630,China)
出处
《中国电子科学研究院学报》
北大核心
2021年第7期692-697,共6页
Journal of China Academy of Electronics and Information Technology
