There has recently been an increase in the number of RDF knowledge bases published on the Internet. These rich RDF data sets can be useful in answering many queries, but much more interesting queries can be answered by integrating data from different data sets. This has given rise to research on automatically linking different RDF data sets representing different knowledge bases. This is challenging due to the scale and semantic heterogeneity of these data sets. Various approaches have been proposed, but there is room for improving the quality of the generated links. In this demonstration, we showcase ALEX, a system that aims at improving the quality of links between RDF data sets by using feedback provided by users on the answers to linked data queries. ALEX starts with multiple RDF data sets that are linked using any automatic linking algorithm. ALEX enables the user to issue queries that integrate data from different data sets, and to provide feedback on the answers to these queries. ALEX uses this feedback to eliminate incorrect links between the data sets and discover new links. In this demonstration, we show ALEX in action on multiple data sets from the Linked Open Data cloud.
['Ahmed El-Roby', 'Ashraf Aboulnaga']
ALEX: Automatic Link Exploration in Linked Data