文章基本信息

标题：PROBABILISTIC KNOWLEDGE BASE SYSTEM FOR FORENSIC EVIDENCE ANALYSIS
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作者：NOOR MAIZURA MOHAMAD NOOR ; SALWANA MOHAMAD @ ASMARA ; MD YAZID MOHD SAMAN 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2014
卷号：59
期号：3
出版社：Journal of Theoretical and Applied
摘要：Crime investigation is a complex task involving huge amounts of information and requiring many different types of expert knowledge. To improve policies and developing effective crime investigation strategies, it is important to understand the processes behind crime. Besides, uncertainty is a common problem in crime investigation. Uncertainties of knowledge in forensic investigation gives a great impact to the decision making process entirely. This paper discusses on representing and calculating probabilistic knowledge for forensic evidence analysis in assisting crime scene investigation. In order to facilitate forensic evidence analysis, a knowledge base system and Bayesian networks have been developed. It describes the process of calculating the probabilities for forensic evidence analysis. In conclusion from the obtained results, it shows that the developed knowledge base can support decision making for uncertainties knowledge in forensic evidence analysis.
关键词：Knowledge Base System; Probabilistic; Crime Investigation; Forensic Evidence Analysis