An Instance-based Approach for Aligning Resources in the LOD Cloud

Linked data has become an essential component in the Semantic Web world. This data is growing into more and more linked instances distributed over different existing ontologies. In this context, there is an important need to improve the interoperability between different ontologies based on term mapping computation. Intensive work has been dedicated to developing very efficient matching algorithms. These methods that rely for instance on graph structures, machine learning, background knowledge, etc. can be considerably improved by the use of the huge amount of links already existing in the Linked Open Data (LOD) cloud. In this book, we will gather data coming from different domains and scattered sources which are related but using different vocabularies making their interoperability very challenging. Most of this data is available as an LOD cloud.