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Discovering and evaluating organizational knowledge from textual data: Application to crisis management
Data & Knowledge Engineering ( IF 2.5 ) Pub Date : 2023-10-27 , DOI: 10.1016/j.datak.2023.102237
Dhouha Grissa , Eric Andonoff , Chihab Hanachi

Crisis management effectiveness relies mainly on the quality of the distributed human organization deployed for saving lives, limiting damage and reducing risks. Organizations set up in this context are not always predefined and static; they could evolve and new forms could emerge since actors, such as volunteers or NGO, could join dynamically to collaborate. To improve crisis resolution effectiveness, it is first important to understand, analyze and evaluate such dynamic organizations in order to adjust crisis management plans and ease coordination among actors. Giving a textual experience feedback from past crisis, the objective of this paper is to discover the organizational structure deployed in the considered crisis and then evaluate it according to a set of criteria. For that purpose, we combine in a coherent framework text and association rule mining for pattern discovery and annotation, and multi-agent system models and techniques for formally building and evaluating organizational structures. We present the OSminer algorithm that discovers association rules based on relevant textual patterns and then builds an organizational structure including three main relations between actors: power, control and coordination. A real-life case study, a flood crisis hitting the south west of France, serves as a basis for testing/experimenting our solution. The organizational structure, discovered in this case study, has 24 actors. Its evaluation indicates its efficiency, but shows that it is neither robust nor flexible. Our findings highlight the potential of our approach to discover and evaluate organizational structures from a text recording interactions between stakeholders in a crisis context.



中文翻译:

从文本数据中发现和评估组织知识:在危机管理中的应用

危机管理的有效性主要取决于为拯救生命、限制损害和降低风险而部署的分布式人力组织的质量。在这种情况下建立的组织并不总是预先定义的和静态的;由于志愿者或非政府组织等参与者可以动态地加入协作,因此它们可以不断发展,新的形式也可以出现。为了提高危机解决的有效性,首先需要了解、分析和评估这些动态组织,以便调整危机管理计划并简化参与者之间的协调。本文的目的是根据过去危机的文本经验反馈,发现在所考虑的危机中部署的组织结构,然后根据一组标准对其进行评估。为此,我们将用于模式发现和注释的文本和关联规则挖掘以及用于正式构建和评估组织结构的多智能体系统模型和技术结合在一个连贯的框架中。我们提出了OSminer算法,该算法根据相关文本模式发现关联规则,然后构建一个组织结构,包括参与者之间的三种主要关系:权力、控制和协调。现实生活中的案例研究(法国西南部发生的洪水危机)可以作为测试/实验我们的解决方案的基础。本案例研究中发现的组织结构有 24 个参与者。它的评估表明了它的效率,但表明它既不稳健也不灵活。我们的研究结果凸显了我们的方法在危机背景下从记录利益相关者之间互动的文本中发现和评估组织结构的潜力。

更新日期:2023-10-29
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