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Managing Uncertainty in Ontology Mapping in E-Learning Context

机译:在电子学习环境中管理本体映射的不确定性

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Many mapping methods have been proposed in recent years, but every of them works well only for specific type of ontologies or in well-defined context. A grand number of mapping methods propose mappings, leading to inconsistency of resulting ontological network, and in such a way make it unusable in many reasoning-based applications. And most of automatically proposed mappings are uncertain in some sense. In this paper we make a short analysis of the approaches for modelling ontology mapping uncertainty and the ways for detecting logical errors, resulting from incorrect mappings. We discuss some important mapping, mapping evaluation and refinement strategies, well working in e-learning domain.
机译:近年来,已经提出了许多映射方法,但是它们中的每一种仅适用于特定类型的本体或定义良好的上下文。大量的映射方法提出了映射,从而导致了生成的本体网络的不一致,并且以这种方式使其无法在许多基于推理的应用程序中使用。从某种意义上讲,大多数自动建议的映射都是不确定的。在本文中,我们简要分析了用于建模本体映射不确定性的方法以及检测由于错误映射而导致的逻辑错误的方法。我们讨论了一些重要的映射,映射评估和优化策略,以及它们在电子学习领域中的良好运作。

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