基于本体支持多移动决策者的协同决策框架

Hyun Jung Lee, Mye M. Sohn
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摘要

我们提出了一个框架来支持多移动用户之间的协作决策。该框架由智能体基于案例的推理、集成本体生成和价值统一模块组成。基于案例的推理模块用于语义相似度计算,用于从每个决策者的案例库中提取最相似的案例。每个最相似的情况都可以作为新需求的备选解决方案,从而使决策者之间进行协作决策。备选解决方案的数量取决于协作决策者的数量。每个提取的案例都映射到个性化的个人本体上,方法是将每个案例投影到元本体上,以便为新需求导出适当的解决方案。个人本体由所有个性化个人本体中常见的类和/或实例及其关系组成。它被命名为集成本体。下一步,为了找到一个令人满意的协作解决方案,我们需要确定集成本体上的类或实例的统一程度。统一的权重意味着类和/或实例在决策者之间共享的程度。使用集成本体,通过统一权值最大的值进行统一传播。统一将递归地执行,直到达成协作决策。为此,我们提出了基于本体的值统一算法。但是,如果在统一完成后无法找到解,则采用我们新提出的实时交互协商算法。
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Collaborative Decision-Making Framework for Supporting Multi-mobile Decision-Makers Using Ontology
We propose a framework to support collaborative decision-making among multi-mobile users. This framework is comprised of an Agent's Case-based Reasoning, Integrated Ontology Generation and a Value Unification Module. The case-based reasoning module used to semantic similarity calculation and is applied to the extraction of the most similar case from each decision maker's case-base. Each the most similar case can be an alternative solution for the new requirement which makes the collaborative decision among the decision-makers. The number of alternative solutions depends on the number of the collaborative decision-makers. Each extracted case is mapped on a personalized personal ontology by projecting each of the cases onto the meta-ontology for deriving an appropriate solution for the new requirement. The personal ontology consists of the classes and/or instances and their relationships that are common in all the personalized personal ontologies. It is named an integrated ontology. As the next step, to find a collaboratively satisfactory solution, we need to determine the degree of unification of classes or instances on the integrated ontology. The weight of unification means the extent to which the classes and/or instances are shared among the decision-makers. The propagation of unification is performed by the value that has maximum weight of unification using the integrated ontology. The unification is executed recursively until it reaches a collaborative decision. To do so, we propose the ontology-based value unification algorithm. However, if we cannot find the solution after the unification is finished, the real-time interactive negotiation algorithm that is newly proposed by us is applied.
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