Criminal Investigation Expert System Based on Extension Intelligence
Based on the theoretical research and actual developing status of artificial intelligence and expert system, this paper discusses several issues in the development of criminal investigation expert systems (CIESs). In particular, we focus on an extension decision support system (EDSS) which employs domain knowledge of recidivism in the crime analysis system. Using the elicited domain knowledge, the EDSS tool uses deductive reasoning techniques to make inferences and provide suggestive courses of action to support the investigatory functions of police, attorneys, or probation officials. In this paper, we present an experience mapping intuitive inversion principle (EMU), and we describe the rationale for developing the CIESs, why we focus on the criminal analysis system, the methodology for eliciting EDSS domain knowledge and experience, and a scenario of what we are implementing as a proof of intuition learning system. A series of elicitation sessions which epitomize the EDSS have been discussed in the paper. After presenting an overview of the system and the major research choices, we describe in detail the systems modules and present examples of its potential use.
criminal investigation expert system CDSS extension intelligence artificial intuition knowledge learning
Ping He Zengtang Qu
Department of InformationLiaoning Police Academy Dalian, 116036 China
国际会议
The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)
沈阳
英文
478-481
2010-03-27（万方平台首次上网日期，不代表论文的发表时间）