移动终端冗余运营数据迭代消除仿真研究

Simulation Research on Iterative Elimination of Redundant Operation Data of Mobile Terminals

采用当前方法消除移动终端中存在的冗余运营数据时,不能在较短的时间内彻底的消除移动终端中存在冗余运营数据,存在消除效率低和召回率低的问题。提出移动终端冗余运营数据迭代消除方法,采用主成分分析法对移动终端中存在的高维运营数据做降维处理,根据运营数据的空间距离和运营数据的属性分布相似度得到运营数据之间在移动终端的实距离矩阵,根据实距离矩阵得到运营数据对应的最近邻表,通过元素在最近邻表中的交叉情况计算运营数据间在移动终端中的相似性矩阵,根据计算结果对运营数据做分类处理,将分类后的运营数据依次输入局部过滤器和全局过滤器中,消除移动终端中存在的冗余运营数据。仿真结果表明,所提方法的消除效率高、召回率高。

In the current method, the redundant operation data in mobile terminal cannot be completely eliminated in short time, resulting in low efficiency and low recall rate. In this article, an iterative elimination method for redundant operation data in mobile terminal was put forward. Firstly, the principal component analysis method was used to reduce the dimension of high-dimensional operational data existing in the mobile terminal. According to the spatial distance of operational data and the attribute distribution similarity of operational data, the real distance matrix among operational data in mobile terminal. Based on the real distance matrix, the nearest neighbor table corresponding to the operational data was obtained. Then, similarity matrix among operational data in the mobile terminal was calculated by the intersection situation of elements in the nearest neighbor table. According to the calculation result, the operational data was classified. Finally, the classified operational data was sequentially input into the local filter and the global filter. Thus, the redundant operational data existing in the mobile terminal was eliminated. Simulation results show that the proposed method has high elimination efficiency and high recall rate.