Ontology matching is an integral part for establishing semantic interoperability. One of the
main challenges within the ontology matching operation is semantic heterogeneity, ie …

Establishing identity links across RDF datasets is a central and challenging task on the way
to realising the Data Web project. It is well-known that data supplied by different sources can …

This paper describes the Ontology Alignment Evaluation Initiative 2017.5 pre-campaign.
Like in 2012, when we transitioned the evaluation to the SEALS platform, we have also …

Instance matching (IM) is the process of matching instances across Knowledge Bases (KBs)
that refer to the same real‐world object (eg, the same person in two different KBs). Several …

Background: Ontology matching provides a solution to the semantic heterogeneity problem
by finding semantic relationships between entities of ontologies. Over the last two decades …

A number of real and synthetic benchmarks have been proposed for evaluating the
performance of link discovery systems. So far, only a limited number of link discovery …

Geospatial linked data are an emerging domain, with growing interest in research and the
industry. There is an increasing number of publicly available geospatial linked data …

Entity disambiguation is a widely investigated topic, and many matching algorithms have
been proposed. However, this task has not yet been satisfactorily addressed when the …

The schema matching task is an integral part of the data integration process. It is usually the
first step in integrating data. Schema matching is typically very complex and time …

Tabular data to Knowledge Graph matching is the process of assigning semantic tags from
knowledge graphs (eg, Wikidata or DB-pedia) to the elements of a table. This task is a …