基于上下文对象数据库的社会结构挖掘

Tingting Fu
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引用次数: 0

摘要

随着计算机、硬件和无线通信技术的进步,物联网、社交网络等新词进入了我们的日常生活。无线传感器网络和物联网等相关领域正在改变我们的日常生活。上下文感知是未来应用程序(如基于位置的服务和社会信息传递)成功的关键。如何有效地存储和管理这些上下文信息是本文研究的热点。为了支持社会信息路由,提出了一种基于不平衡滑动窗口的社会结构挖掘算法。我们还提出了上下文对象数据库(COD)的新概念,用于存储和管理时间、位置、交互等各种上下文信息和对象。本文主要讨论了COD的基本结构——不平衡滑动窗口模型。讨论了COD的应用,如利用滑动窗口模型挖掘社会结构。仿真结果表明,该方法具有较高的社区发现精度和较低的数据处理量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mining Social Structure on Context Objects Database
The advance of computing, hardware and wireless communication technologies has put the new words— Internet of Things, Social Networks into our daily life. Related areas such as Wireless Sensor Networks and Internet of Things have been changing our daily lives. Context awareness is the key to the success of prospective applications, such as location based services and social information delivery. This paper focuses on the hot topic of how to store and manage this context information efficiently. To support social information routing, this paper brought forward an unbalanced slid- ing window based social structure mining algorithm. We also developed new concept of Context Objects Database, COD, which stored and managed various context information and objects such as time, location, interaction and so on. The pa- per mainly discusses the unbalanced sliding window model, fundamental architecture of COD. We also discuss the appli- cation of the COD such as mining social structure using sliding window model. The simulation results show that the pro- posed method has better accuracy of social communities discovery and lower data amount processed.
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