论文标题
探索瓦斯坦的距离跨越概念嵌入的距离
Exploring Wasserstein Distance across Concept Embeddings for Ontology Matching
论文作者
论文摘要
测量本体学元素之间的距离对于本体匹配是基础。基于字符串的距离指标对于浅层句法匹配是臭名昭著的。在这项探索性研究中，我们研究了瓦斯汀距离靶向连续空间的距离，这些空间可以包含各种类型的信息。我们使用预训练的单词嵌入系统嵌入本体元素标签。我们研究了Wasserstein距离在衡量本体论之间相似性以及在各个元素之间发现和完善匹配的有效性。与领先的系统相比，我们对OAEI会议轨道和MSE基准的实验取得了竞争成果。
Measuring the distance between ontological elements is fundamental for ontology matching. String-based distance metrics are notorious for shallow syntactic matching. In this exploratory study, we investigate Wasserstein distance targeting continuous space that can incorporate various types of information. We use a pre-trained word embeddings system to embed ontology element labels. We examine the effectiveness of Wasserstein distance for measuring similarity between ontologies, and discovering and refining matchings between individual elements. Our experiments with the OAEI conference track and MSE benchmarks achieved competitive results compared to the leading systems.
