评估语义映射

D. Wardani
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引用次数: 0

摘要

随着数据网络中链路的重要性日益提高,在关系图映射模型中应更多地考虑链路。在映射过程中,将现实世界中的链接映射为图模型中的节点时,经常会出现语义抽象缺口。本文的重点是在不丢失语义的情况下评估映射和转换的结果。我们建议使用schema.org作为语义标准来评估我们的方法。在三个数据集上的实验表明,语义映射方法是非常有效的。我们在不考虑差距指数(平均值为0.6922)和考虑差距指数(平均值为0.5264)的情况下获得了相当好的分数匹配,平均精度分数0.7042也很不错。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating The Semantic Mapping
Along the increasing of the importance of links in the network of data, they should be considered more in the mapping relational to graph model. Semantic abstraction gaps often occur during the mapping process where the link in the real world is mapped as a node in a graph model. This paper focused on evaluating the result of mapping and converting without losing the semantics. We propose the evaluation of our approach by using schema.org as the semantic standard. The experiments in three data sets show that the semantic mapping approach is pretty effective. We obtain quite good score matching without considering the gap index (the average is 0.6922) and with considering the gap index (the average is 0.5264) and the average precision score, 0.7042, is pretty good too.
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