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Integrating textual analysis and evidential reasoning for decision making in Engineering design

机译：将文本分析和证据推理相结合来进行工程设计决策

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摘要

Decision making is an important element throughout the life-cycle of large-scale projects. Decisions are critical as they have a direct impact upon the success/outcome of a project and are affected by many factors including the certainty and precision of information. In this paper we present an evidential reasoning framework which applies Dempster-Shafer Theory and its variant Dezert-Smarandache Theory to aid decision makers in making decisions where the knowledge available may be imprecise, conflicting and uncertain. This conceptual framework is novel as natural language based information extraction techniques are utilized in the extraction and estimation of beliefs from diverse textual information sources, rather than assuming these estimations as already given. Furthermore we describe an algorithm to define a set of maximal consistent subsets before fusion occurs in the reasoning framework. This is important as inconsistencies between subsets may produce results which are incorrect/adverse in the decision making process. The proposed framework can be applied to problems involving material selection and a Use Case based in the Engineering domain is presented to illustrate the approach.
机译：决策是整个大型项目生命周期中的重要元素。决策至关重要，因为它们直接影响项目的成功/结果，并受许多因素的影响，包括信息的确定性和准确性。在本文中，我们提供了一个证据推理框架，该框架运用Dempster-Shafer理论及其变体Dezert-Smarandache理论来帮助决策者做出可能不精确，矛盾和不确定的知识的决策。该概念框架是新颖的，因为基于自然语言的信息提取技术被用于从各种文本信息源中提取和估计信念，而不是假设这些估计已经给出。此外，我们描述了在推理框架中发生融合之前定义一组最大一致性子集的算法。这很重要，因为子集之间的不一致可能会产生决策过程中不正确/不利的结果。所提出的框架可以应用于涉及材料选择的问题，并基于工程领域的用例进行了说明。

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