Efficient Index Structures for Node Search of RDF Graphs

Abstract

Published RDF data on the Web have been increasing, and it is important to execute data mining and machine learning on RDF graphs. Most RDF stores build index structures for efficient storages and retrieval of huge RDF graphs. However, it is inefficient because multiple indexes are required to match any triple patterns, and duplicate results in neighbor node search for data mining and machine learning feature extraction. In this work, we propose index structures called a P-Link index for fast query resolving and efficient data storing.The P-link index focuses on the fact that the subject and object of a triple are nodes of an RDF graph, it has an index structure for node search, and predicate links for matching any triple pattern. Our experiments show that the P-Link index with an index structure reduces the memory space and efficiently executes specific search tasks such as node search.