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预测OWL推论的可理解性

Predicting the Understandability of OWL Inferences
课程网址: http://videolectures.net/eswc2013_power_owl_inferences/  
主讲教师: Richard Power
开课单位: 英国开放大学
开课时间: 2013-07-08
课程语种: 英语
中文简介:
在本文中,我们描述了一种预测OWL推理的可理解性水平的方法。具体而言,我们提出了一种概率模型,用于基于对个体推理步骤的可理解性的测量来测量多步推理的可理解性。我们还提出了一项评估研究,该研究证明我们的模型与OWL的两步推理相对较好。这个模型已经应用于我们的研究中,为OWL本体的蕴含生成可访问的解释,以确定替代方案中最容易理解的推理,从中产生最终解释。
课程简介: In this paper, we describe a method for predicting the understandability level of inferences with OWL. Speci cally, we present a probabilistic model for measuring the understandability of a multiple step inference based on the measurement of the understandability of individual inference steps. We also present an evaluation study which con rms that our model works relatively well for two-step inferences with OWL. This model has been applied in our research on generating accessible explanations for an entailment of OWL ontologies, to determine the most understandable inference among alternatives, from which the nal explanation is generated.
关 键 词: OWL推理; 概率模型; 替代方案
课程来源: 视频讲座网
最后编审: 2020-09-18:chenxin
阅读次数: 75