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Analysis of a Web Content Categorization System Based on Multi-agents

机译:基于多智能体的Web内容分类系统分析

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摘要

This paper presents a Multi-Agent based web content categorization system. The system was prototyped using an Agents' Framework for Internet data collection. The agents employ supervised learning techniques, specifically text learning to capture users preferences. The Framework and its application to E-commerce are described and the results achieve during the IST DEEPSIA project are shown. A detailed description of the most relevant system agents as well as their information flow is presented. The advantages derived from agent's technology application are conferred.
机译:本文提出了一种基于Multi-Agent的Web内容分类系统。该系统是使用Agents的Internet数据收集框架进行原型设计的。代理采用监督学习技术,特别是文本学习来捕获用户的偏好。描述了该框架及其在电子商务中的应用,并显示了IST DEEPSIA项目期间取得的成果。介绍了最相关的系统代理及其信息流的详细说明。赋予了代理商技术应用带来的优势。

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