TY - JOUR A2 - Khan Habib Ullah AU - Khan Nauman Ali AU - Zhang Sihai AU - Zhou Wuyang AU - Almogren Ahmad AU - Ud Din Ikram AU - AsifSP - 6667610 VL - 2020 AB -基于随机物联网(IoT)的通信行为对社会网络产生了巨大的影响。社交网络的发展有助于量化社交物联网(social Internet of Things, SIoT)的影响。两个人在不同地理位置、不同时间框架下的多重存在暗示了对社会联系的预测。我们研究的是人们之间的社会关系在多大程度上可以通过批判性地回顾社会网络来推断。我们的研究使用了基于中国电信的匿名呼叫数据记录(cdr)和两个开放的基于位置的社交网络数据集Brightkite和Gowalla。我们的研究基于移动通信数据识别社会关系，并进一步利用地理位置的通信原因。本文提出了一个基于管道和过滤器架构的推理框架，该框架将缺失的关系预测为可疑的社会关系。它突出了真实数据中不存在的用户之间的秘密关系。拟议的框架包括两个主要部分。 Firstly, users’ cooccurrence based on the mutual location in a specific time frame is computed and inferred as social ties. Results are investigated based upon the cooccurrence count, the gap time threshold values, and mutual friend count values. Secondly, the detail about direct connections is collected and cross-related to the inferred results using Precision and Recall evaluation measures. In the later part of the research, we examine the false-positive results methodically by studying the human cooccurrence patterns to identify hidden relationships using a social activity. The outcomes indicate that the proposed approach achieves comprehensive results that further support the theory of suspicious ties. SN - 1058-9244 UR - https://doi.org/10.1155/2020/6667610 DO - 10.1155/2020/6667610 JF - Scientific Programming PB - Hindawi KW - ER -