应用大数据实现社交网络的多模型聚类(从数据中获取知识)

I. Khaimovich, V. M. Ramzaev, V. G. Chumak
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引用次数: 1

摘要

所开发的方法为两个基本任务提供了解决方案,从而揭示了大数据技术的灵知学潜力:基于识别社会共鸣条件的模型的信息社会三个最重要领域的社会预测;基于使用基于大数据技术的社交网络多模式集群的适当管理选项,成功实施社会抑制程序。本文提出了有助于提高该地区社会抑制领域工作效率的工具。本文提出的调控方法对于控制形式多样、要素范围广泛的区域性社会抑制过程,以及生命活动的生长动态和主动转化都是有效的。同时,使用现代产品可以实时评估和显示变化,这对地方政府当局很有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multimodel clustering of social networks in social dampening applying BIG DATA (acquiring knowledge from data)
The developed methodology provides a solution to two essential tasks, thereby revealing the gnoseological potential of Big Data technology: social forecasting in the three most significant areas of the information society based on a model which identifies conditions for social resonance; successful implementation of the social dampening procedure based on the use of appropriate management options using multimodal clusterization of social networks based on Big Data technology. The article suggests the tool that helps to increase work efficiency in the sphere of social dampening in the region. The proposed method of regulation may be efficient when it comes to the control of the regional social dampening processes which have variety of forms and broad range of elements and factors, as well as growth dynamics and active transformation of life activities. At the same time using modern products make it possible to evaluate and show changes on a real-time basis which can be useful for local government authorities.
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