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Key technologies research of network information filtering based on Improved Genetic Algorithms

机译:基于改进遗传算法的网络信息过滤关键技术研究

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Along with the development of the Internet, how to manage and control network information resources effectively has become a hot research. In this paper, we discussed key technologies of network information filtering: feature selection and learning algorithm. Based on feature subset generated by feature selection would affect the filtering accuracy, we proposed an improved feature selection method CHIIDF, using this method to remove redundant features, then using annealing genetic algorithm to learn and to get user profile. Finally, we developed the system of network information filtering and analyzed the data that achieved good results.
机译:随着Internet的发展,如何有效地管理和控制网络信息资源已经成为研究的热点。在本文中,我们讨论了网络信息过滤的关键技术:特征选择和学习算法。基于特征选择产生的特征子集会影响过滤精度,我们提出了一种改进的特征选择方法CHIIDF,该方法用于去除多余特征,然后利用退火遗传算法学习并获取用户信息。最后,我们开发了网络信息过滤系统,并分析了取得良好效果的数据。

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