论文标题
通过将多个本体论与Comerger合并：一种基于分区的方法来建立知识
Towards Building Knowledge by Merging Multiple Ontologies with CoMerger: A Partitioning-based Approach
论文作者
论文摘要
本体论是在语义网中组织数据的主要方式。通常，有必要将几个独立发展的本体论结合起来，以获取完全代表感兴趣领域的知识图。通过合并，现有本体论的互补性可以利用。现有的本体合并方法主要实施二进制合并。但是，随着跨领域相关本体论的数量和规模的增长，可伸缩性成为核心挑战。多主体学合并技术为这一问题提供了潜在的解决方案。我们提出Comerger，这是一种可扩展的多个本体合并方法。为了有效的处理，我们没有依次合并完整的本体，我们将跨本体的相关概念分为分区，然后首先合并在这些分区内，然后将其合并。知名数据集的实验结果证实了我们方法的可行性，并证明了其优越性比二进制策略的优势。通过实时Web门户可以自由访问典型的实现。
Ontologies are the prime way of organizing data in the Semantic Web. Often, it is necessary to combine several, independently developed ontologies to obtain a knowledge graph fully representing a domain of interest. The complementarity of existing ontologies can be leveraged by merging them. Existing approaches for ontology merging mostly implement a binary merge. However, with the growing number and size of relevant ontologies across domains, scalability becomes a central challenge. A multi-ontology merging technique offers a potential solution to this problem. We present CoMerger, a scalable multiple ontologies merging method. For efficient processing, rather than successively merging complete ontologies pairwise, we group related concepts across ontologies into partitions and merge first within and then across those partitions. The experimental results on well-known datasets confirm the feasibility of our approach and demonstrate its superiority over binary strategies. A prototypical implementation is freely accessible through a live web portal.
