预测分析系统:人工智能缉毒技术的案例研究

M. Abramson, S. Bennett, W. Brooks, E. Hofmann, P. Krause, A. Temin
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引用次数: 1

摘要

预测分析系统(PANS)利用对毒品贩运行为的了解,帮助分析人员将所有来源的数据融合成连贯的活动图像,从而可以自动预测未来的事件。该系统使用一种基于模型的推理、计划识别的形式,将实际活动的报告与预期活动相匹配。该模型结合了几组领域约束,并使用约束传播算法将已知数据点投影到未来(即预测未来事件)。该系统可以同时跟踪许多可能性,还允许分析人员对活动进行假设,并观察假设对未来活动的可能影响。它利用知识表示、计划识别和机器学习方面的最新成果来获取分析师的专业知识,而不会受到基于规则的专家系统的脆弱性的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Analysis System: a case study of AI techniques for counternarcotics
The Predictive Analysis System (PANS) uses knowledge of narco-trafficking behaviors to help analysts fuse all-source data into coherent pictures of activity from which predictions of future events can be made automatically. The system uses a form of model-based reasoning, plan recognition, to match reports of actual activities to expected activities. The model incorporates several sets of domain constraints and a constraint propagation algorithm is used to project known data points into the future (i.e., predict future events). The system can track many possibilities concurrently, and also allows analysts to hypothesize activity and observe the possible effect of the hypotheses on future activities. It makes use of recent results in knowledge representation, plan recognition, and machine learning to capture analysts' expertise without suffering from the brittleness of rule-based expert systems.<>
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