Reactive web policing based on self-organizing maps

A. Chan, A. Shiu, Jiannong Cao, H. Leong
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引用次数: 3

Abstract

Almost without any doubt, the Internet and Web in particular, have brought about radical changes in information retrieval with unparallel benefits to organizations and individuals to gain access to vast amount of articles and documents. The focus on restricting inappropriate materials at their source is not well suited to the nature and open architecture of Internet, where information source maybe in a different legal jurisdiction than the recipient. This paper proposes a reactive approach based on SOM (Self-Organising Maps) neural network to deal with dynamic blocking and filtering of Internet contents. We describe the design and implementation of a web policing proxy (WebPolice) based on a Kohonen's neural network model that attempts to classify the web contents dynamically using competitive learning. The parameter setting of the network has been experimented to obtain the optimal classification rate and performance for the model.
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基于自组织地图的响应式网络监管
几乎毫无疑问,Internet和Web给信息检索带来了根本性的变化,给组织和个人获取大量文章和文档带来了无与伦比的好处。注重从源头上限制不适当的材料不太适合互联网的性质和开放架构,因为信息来源可能与接收方处于不同的法律管辖范围。本文提出了一种基于自组织地图(SOM)神经网络的响应式方法来处理互联网内容的动态拦截和过滤。我们描述了基于Kohonen神经网络模型的web监管代理(WebPolice)的设计和实现,该模型试图使用竞争学习动态地对web内容进行分类。对网络的参数设置进行了实验,以获得模型的最佳分类率和性能。
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