Abstract: Due to low productivity and low efficiency, artificial processing holds back Search Engine Optimization (SEO). In order to deal with it, a network propaganda machine model based on SEO analysis was proposed, and its main idea, key algorithms and working flows were described in this paper. Further, backward spider technology was utilized to collect sorted information and to search optimized key words by matching operations worked in an overlay space. Then, Monte Carlo algorithm was atopted to estimate all characters and to prove the accuracy and efficiency. The simulation comparisons show that the proposed model has better sort performance and clients satisfaction than the traditional one.

Key words: Search engine optimization, network, Propaganda machine, Subject, matching

摘要： 针对搜索引擎优化过程中的人工控制方式处理效率低下，可靠性差等问题，提出了自动实现网站信息优化的网络宣传机模型，给出了该模型的主要思想、关键算法以及运行流程。该模型采用反向爬虫技术收集收录排名等信息，并通过主题词叠加空间中的匹配操作，选择优化主题词；同时，网络宣传机采用蒙特卡罗算法实现匹配特征测度，提高了匹配效率与精度。仿真实验对比证明，该模型具有较好的搜索引擎排名提升能力和客户满意度。

关键词: 搜索引擎优化, 网络, 宣传机, 主题词, 匹配