以微信为代表的通信工具每天都在产生可以描述人物关系的海量数据,如何通过数据整合为侦查办案提供智力资源和知识服务已成为大数据环境下公安机关科研工作的研究重点和难点内容.本文以微信聊天记录的时间信息为研究对象,利用分层聚类和K-均值聚类分析技术,发现通信时间特征与人物关系之间的关联关系,将微信联系人按照"亲疏远近"的人物关系进行分类,从而为案件侦查过程中快速寻找犯罪团伙、重点嫌疑对象提供一种新的技术手段.%Wechat, presently one of the most popular communication tools, is everyday generating huge quantity of data that can be used to profile people's relationship. Therefore, it is becoming the research focal points, albeit also difficult to attain, that how to integrate and mine the massive data is about to provide intelligent source and knowledge service for criminal cases investigation. In this paper, the time information was taken as the studied subject that was extracted from the Wechat's record so that the relationships of Wechat's contractors can be classified through finding the correlative time characteristics by Hierarchical clustering and K-means clustering analyses. Thus, this research is potential of providing new resorts for quickly searching criminal gangs or key suspects during case investigation.
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