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首页> 外文期刊>International Journal of Business Intelligence and Data Mining >Genetic algorithm-based intelligent multiagent architecture for extracting information from hidden web databases
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Genetic algorithm-based intelligent multiagent architecture for extracting information from hidden web databases

机译:基于遗传算法的智能多主体架构,可从隐藏的Web数据库中提取信息

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摘要

Though there are enormous amount of information available in the web, only very small portion of the available information is visible to the users. Due to the non-visibility of huge information, the traditional search engines cannot index or access all information present in the web. The main challenge in the mining of the relevant information from a huge hidden web database is to identify the entry points to access the hidden web databases. The existing web crawlers cannot retrieve all information from the hidden web databases. To retrieve all the relevant information from the hidden web, this paper proposes an architecture that uses genetic algorithm and intelligent agents for accessing hidden web databases. The proposed architecture is termed as genetic algorithm-based intelligent multi-agent system (GABIAS). The experimental results show that the proposed architecture provides better precision and recall than the existing web crawlers.
机译:尽管网络中有大量可用信息,但用户只能看到很小一部分可用信息。由于无法看到大量信息,因此传统的搜索引擎无法索引或访问网络中存在的所有信息。从庞大的隐藏Web数据库中挖掘相关信息的主要挑战是识别访问隐藏Web数据库的入口点。现有的Web搜寻器无法从隐藏的Web数据库检索所有信息。为了从隐藏的网络中检索所有相关信息,本文提出了一种使用遗传算法和智能代理访问隐藏的网络数据库的体系结构。所提出的体系结构被称为基于遗传算法的智能多主体系统(GABIAS)。实验结果表明,所提出的体系结构比现有的Web搜寻器提供了更好的精度和召回率。

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