求翻译：摘　要 SOM 算法作为一种聚类和高维可视化的无监督学习算法，是通过模拟人脑对信号处理的特点而发展起来的一种人工神经网络，它可以很好的用来构建知识地图。由于对等网络具有分散式控制、自组织、自适应和良好的扩展性等优点，这使得它非常适合用来处理因特网中海量主机资源。本文介绍了基于 SOM 算法的知识地图在对等网络中的研究，采用某研究院的研究报告摘要生成知识地图。从评价实验结果显示 ESOM 是能够与其他对等节点中阐明的同时保留个别对等方的知识结构认知知识网络。是什么意思？

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Summary * SOM algorithms together as a class, and high-dimensional visualization of the supervision learning algorithms without using the analog, it is the human brain signal processing features such as development of an artificial neural network, it can be used to build a good knowledge maps. Becau

Summary SOM algorithm as a cluster and unsupervised learning algorithm for high-dimensional visualization is through simulated human brain on signal processing characteristics of the development of an artificial neural network, it can be better used to build the knowledge map. Because of the decentr