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Intelligent Information Retrieval Model Based on Multi-Agents

机译:基于多Agent的智能信息检索模型

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摘要

Information Retrieval in the World Wide Web (WWW) using the general search engines is still a difficult and time-consuming task, which creates a demand of new information search and retrieval techniques. An intelligent retrieval system model based on multi-agent is proposed which assists the user in finding interesting information in the WWW. This model searches through the popular and special Web search engines, filters their result, and lists to the user a reduced number of information with high probability of being relevant to him. This filtering is implemented by the agent analyzing the user''s behavior on the Web based on user''s search intent and preferences. The design, the architecture, the functional components and the workflow of the model are elaborated. The model is helpful to solve the shortcomings effectively of low precision and relevant document ranking behind in general search engine.
机译:使用常规搜索引擎在万维网(WWW)中进行信息检索仍然是一项困难且耗时的任务,这对新的信息搜索和检索技术提出了要求。提出了一种基于多智能体的智能检索系统模型,该模型可以帮助用户在WWW中找到有趣的信息。该模型通过流行和特殊的Web搜索引擎进行搜索,过滤其结果,并向用户列出数量减少的信息,这些信息与他有关的可能性很高。通过代理基于用户的搜索意图和首选项分析用户在Web上的行为来实现此筛选。阐述了模型的设计,架构,功能组件和工作流程。该模型有助于有效地解决精度低和相关文档在通用搜索引擎中落后的缺点。

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