Predictive Analytics Using a Blackboard-Based Reasoning Agent

Jia Yue, A. Raja, W. Ribarsky
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引用次数: 5

Abstract

Significant increase in collected data for investigative tasks and the increased complexity of the reasoning process itself have made investigative analytical tasks more challenging. These tasks are time critical and typically involve identifying and tracking multiple hypotheses; gathering evidence to validate the correct hypotheses and eliminating the incorrect ones. In this paper we specifically address predictive tasks that are concerned with predicting future trends. We describe RESIN, an AI blackboard-based agent that leverages interactive visualizations and mixed-initiative problem solving to enable analysts to explore and pre-process large amounts of data in order to perform predictive analytics. Our empirical evaluation discusses the advantages and challenges of predictive analytics in a complex domain like intelligence analysis.
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使用基于黑板的推理代理进行预测分析
调查任务收集的数据显著增加,推理过程本身的复杂性增加,使调查分析任务更具挑战性。这些任务时间紧迫,通常涉及识别和跟踪多个假设;收集证据来验证正确的假设,并排除不正确的假设。在本文中,我们特别讨论了与预测未来趋势有关的预测任务。我们描述了RESIN,一个基于人工智能黑板的代理,它利用交互式可视化和混合主动问题解决方案,使分析师能够探索和预处理大量数据,以便执行预测分析。我们的实证评估讨论了预测分析在智能分析等复杂领域的优势和挑战。
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