Modeling of distributed visual knowledge discovery from data process

Hamdi Ellouzi, Mounir Ben Ayed, Hela Ltifi
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Abstract

Assigning a set of intelligent agents in each phase of the Knowledge Discovery from Data (KDD) process improves communication and cooperation between the different KDD steps in order to generate relevant results knowledge for decision-making tasks. We aim in particular to simulate the behavior of a KDD system in which specific intelligent agents interact with each other and with their environment. Such environment is characterized by its dynamic, visual and real-time aspects. The proposed approach is applied to develop a prototype for the fight against nosocomial infections in the hospital Intensive Care Units. This paper ends with the evaluation of the prototype usability.
基于数据过程的分布式可视化知识发现建模
在数据知识发现过程的每个阶段分配一组智能代理,可以改善不同数据知识发现步骤之间的沟通和合作,从而为决策任务生成相关的结果知识。我们的特别目标是模拟一个KDD系统的行为,在这个系统中,特定的智能代理彼此之间以及与它们的环境之间进行交互。这种环境具有动态性、可视性和实时性等特点。所提出的方法被应用于开发一个原型,用于对抗医院重症监护病房的医院感染。最后对原型的可用性进行了评价。
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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