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Research on Influence Pattern for Internet Association Relation Monitoring

机译:互联网关联关系监控的影响模式研究

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The Internet shows more about information sharing, communication and freedom from Web to Web 2.0.However, there are challenges on the monitoring the influence structure of the negligible individuals on the web. This paper defines the "close relationship" between social individuals hidden in variety of communication medias of Internet, designs a novel intelligent association relation mining mechanism for removing the fault influence of non-valuable high frequency to improve the information quality measure of the "close relationship"; also, this paper introduces Interpretive Structural Model (ISM) to explore the power of the influence, the central figures and their close relationships, to discover the pattern and channel for information flow between the social individuals in the network. The model is suitable to relation structure mining in many kinds of networks and medias and to reveal the important relations and their influences in the virtual networks. The experiments on the original data show that the feasibility of the whole model in this paper is satisfactory.
机译:互联网展示了有关从Web到Web 2.0的信息共享,通信和自由的更多信息。但是,在监视可忽略个人在Web上的影响力结构方面存在挑战。本文定义了隐藏在互联网各种通信媒体中的社会个体之间的“亲密关系”,设计了一种新型的智能关联关系挖掘机制,消除了无价高频的故障影响,从而改善了“亲密关系”的信息质量测度。 “;此外,本文还介绍了解释性结构模型(ISM),以探索影响力,中心人物及其紧密关系,以发现网络中社会个体之间信息流的模式和渠道。该模型适用于多种网络和媒体中的关系结构挖掘,并揭示了虚拟网络中的重要关系及其影响。对原始数据的实验表明,本文整个模型的可行性是令人满意的。

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