摘要
为了提高分布式融合集成网络网页信息资源定向抽取能力,提出基于卷积神经网络的分布式融合集成网络网页信息资源定向抽取方法。构建分布式融合集成网络网页信息的自适应聚类处理模型,获得分布式融合集成网络网页信息数据集合,采用多重属性调度的方法,建立高分布式融合集成网络网页信息检测的模糊度训练集,实现对网页信息资源的模糊参数辨识与融合,采用最优策略下均衡控制的方法,得到高分布式融合集成网络网页信息的模糊决策特征调度矩阵,通过自相关检测识别与参数寻优的方法实现网页信息资源的定向抽取。仿真结果表明,采用该方法进行网页信息资源定向抽取的精度较高,自适应性较好,提高了网页信息资源定向抽取能力。
In order to improve the directional extraction ability of distributed fusion integrated network Web page information resources,a method of directional extraction of distributed fusion integrated network Web page information resources based on convolutional neural network is proposed.Construct a distributed fusion integrated network Web page information adaptive deletion clustering processing model,obtain a discrete set of distributed fusion integrated network Web page information data,adopt multiple attribute scheduling methods,and establish a highly distributed fusion integrated network Web page information detection ambiguity.The training set realizes the identification and fusion of fuzzy parameters of Web page information resources,adopts the method of balanced control under the optimal strategy,and obtains the fuzzy decision feature scheduling matrix of highly distributed fusion integrated network Web page information,and identifies and optimizes parameters through autocorrelation detection.The method achieves the targeted extraction of Web information resources.The simulation results show that this method has higher accuracy and better adaptability for directional extraction of Web information resources,which improves the ability of directional extraction of Web information resources.
作者
周沭玲
ZHOU Shu-ling(Institute of Artificial Intelligence,Hefei College of Finance&Economics,Hefei 230601,China)
出处
《齐齐哈尔大学学报（自然科学版）》
2021年第4期33-37,53,共6页
Journal of Qiqihar University(Natural Science Edition)
关键词
分布式融合集成网络
卷积神经网络
网页信息资源
定向抽取
distributed converged integrated network
convolution neural network
Web information resources
directional extraction
