J4 ›› 2006, Vol. 28 ›› Issue (6): 102-104.
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赵连朋
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摘要:
本文通过对辅助系统核心功能和侦察决策形成过程的简略探讨,建立了辅助系统的模型框架.在数据挖掘的核心过程中,主要采用数据聚类和关联规则技术,并且通过使用案件侦 破后修正规则库的手段,使辅助系统对规则具有一定的自我学习的智能功能,从而解决了海量的侦察数据与有价值的数据之间的矛盾.
关键词: 数据挖掘 侦察决策 数据聚类 关联规则
Abstract:
By discussing the core functions of an auxiliary system and the decision-making process of an investigation, we build a model framework of the auxiliary system. In the core process of data mining, the techniques of data aggregation and association rules are adopted. And by means of revising the rule library after solving a case, we make the system feature a certain degree of self-learning capability for the rules. Thus the contradictions between the massive investigation data and valuable data are solved,
Key words: data mining, investigation decision-making, data aggregations association rule
赵连朋. 在案件侦察决策中采用数据挖掘技术[J]. J4, 2006, 28(6): 102-104.
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链接本文: http://joces.nudt.edu.cn/CN/
http://joces.nudt.edu.cn/CN/Y2006/V28/I6/102