论文标题
描述逻辑EL ++带有交叉闭合的嵌入
Description Logic EL++ Embeddings with Intersectional Closure
论文作者
论文摘要
许多本体论，特别是在生物医学领域中，基于描述逻辑EL ++。通过分布式表示学习，已经做出了几项努力来解释和利用EL ++的本体论。具体而言，EL ++理论中的概念已被表示为n维嵌入空间内的N球。但是，当使用n球代表概念时，由于两个n球的相交不是n球，因此不满足交叉闭合。在衡量概念与推断概念之间的等价之间的距离时，这会导致挑战。为此，我们开发了EL Box Embedding（Elbe），以使用Axis-Parallel Boxes学习描述逻辑EL ++嵌入。我们从EL ++公理中生成了特殊设计的基于盒子的几何约束，用于模型训练。由于盒子的交点保留为盒子，因此满足了相交的闭合。我们在三个数据集上报告了广泛的实验结果，并提出了一个案例研究，以证明该方法的有效性。
Many ontologies, in particular in the biomedical domain, are based on the Description Logic EL++. Several efforts have been made to interpret and exploit EL++ ontologies by distributed representation learning. Specifically, concepts within EL++ theories have been represented as n-balls within an n-dimensional embedding space. However, the intersectional closure is not satisfied when using n-balls to represent concepts because the intersection of two n-balls is not an n-ball. This leads to challenges when measuring the distance between concepts and inferring equivalence between concepts. To this end, we developed EL Box Embedding (ELBE) to learn Description Logic EL++ embeddings using axis-parallel boxes. We generate specially designed box-based geometric constraints from EL++ axioms for model training. Since the intersection of boxes remains as a box, the intersectional closure is satisfied. We report extensive experimental results on three datasets and present a case study to demonstrate the effectiveness of the proposed method.
