一种基于时序感知的社会网络节点集情境聚合方法

情境聚合是社会感知计算的主要研究工作之一,目前主要采用基于特征提取的方法,对社会的交流方式进行量化分析.但是大多数的研究中忽略了情境信息的时序性,针对社会感知计算中时序情境信息的聚合问题,首先对时序情境和计算情境的聚合过程进行探讨,提出基于时序扩展的计算情境元素,用于情境对象的聚合,并给出一种时序感知的社会网络节点集情境聚合方法.实验表明,该方法能够根据时间情境和计算情境元素的特点,把聚合对象划分为相对情境聚合对象和绝对情境对象,有效地对社会环境中的时序信息进行情境聚合.

Based Time-Series Aware of Social Network Nodes Set Context Aggregation Method

Context aggregation is one of the main tasks of social aware computing. At present it mainly uses feature based extraction to quantitatively analyze social communication. However the evolution process in context aggregation is usually ignored in most studies, this paper specifically explores the fusion process of time context and computing context, and introduces the timing based context element of extension computing in context object aggregation. Through experiments, this method divides aggregation object into relative aggregation object and absolute context aggregation according to the characteristics of the timing and computing contexts. The above can aggregate the social fusion process of time context effectively.