Optimized Processing of Subscriptions to DBpedia Live.

DBpedia Live enables access to structured data extracted from Wikipedia in real-time. A data stream that is generated from Wikipedia changes is instantly loaded in the DBpedia RDF store. Applications can benefit by subscribing to the RDF update stream and receive continuous results from DBpedia. Providing a continuous update stream of changes to subscribed DBpedia queries is a challenging task due to the load it places on the RDF store. In this paper, we propose an optimization approach for processing subscriptions to DBpedia Live. By monitoring the change data stream, query processing can be optimized to avoid unnecessary processing load by continuous database polling. Queries are only re-processed when the system can detect a relation between incoming changes and queries so that it can trigger the processing of the specific query. We evaluated our approach by using a recorded history of the DBpedia change stream and as queries we used the most frequent DBpedia SPARQL queries obtained from the logs. A comparison of our approach to the interval-based database polling approach shows a significant optimization of processing costs.