Compressed Indexes for Fast Search of Semantic Data

The sheer increase in volume of RDF data demands efficient solutions for the triple indexing problem, that is to devise a compressed structure compactly represent triples by guaranteeing, at same time, fast pattern matching operations. This problem lies heart delivering good practical performance resolution complex SPARQL queries on large datasets. In this work, we propose trie-based index layout solve and introduce two novel techniques reduce its space representation improved effectiveness. extensive experimental analysis, conducted over wide range publicly available real-world datasets, reveals our best space/time trade-off configuration substantially outperforms existing state-of-the-art, taking 30-60 percent less speeding up query execution factor 2 - 81×.