Detective DSS Based on Content Cognition Technology

Kairong Li, Juanni Wang, Weiying Gao, Xiaoyan Liu
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Abstract

At present, some problems have emerged in the detection systems such as collecting incomprehensive evidence, over-reliance on the confessions and other problems. All of these problems stem from data can not be shared. To eliminate this disadvantage, this paper proposed a detective decision support system (DSS) based on content cognition technology. Ontology is used to describe concepts and the interrelationships in a specify field, or even in a wider range, it can make these concepts and relations have common recognized, clear and the single definitions in the sharing range. This paper summarizes the problems existed in the detection systems, then proposes ontology and discusses the method to construct the domain ontology [1]. This paper designs a detective decision-making Data Warehouse model which based on ontology, and also gives an example to verify the feasibility and innovation of this approach.
基于内容认知技术的侦探决策支持系统
目前,侦查系统中存在证据收集不全面、过度依赖口供等问题。所有这些问题都源于数据不能共享。为了消除这一缺点,本文提出了一种基于内容认知技术的侦探决策支持系统(DSS)。本体用于描述某一特定领域甚至更广范围内的概念和相互关系,它可以使这些概念和关系在共享范围内具有共同认可的、明确的和单一的定义。本文总结了检测系统存在的问题,提出了本体,并讨论了构建领域本体的方法[1]。本文设计了一种基于本体的检测决策数据仓库模型,并通过实例验证了该方法的可行性和创新性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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