%0 Conference Paper %1 Abdullah:2012:EMS %A Abdullah, Haris %A Rinne, Mikko %A Törmä, Seppo %A Nuutila, Esko %B Proceedings of the 27th Annual ACM Symposium on Applied Computing %C New York, NY, USA %D 2012 %I ACM %K Application Financial Inference Rete Stock %P 372--377 %R 10.1145/2245276.2245348 %T Efficient Matching of SPARQL Subscriptions using Rete %X Ubiquitous domains such as smart spaces, location-aware mobile systems, or internet-of-things are characterized by large and volatile sets of heterogeneous and independently behaving entities like devices, services, and other identified objects. This study focuses on efficient implementation of an event processing system to manage interaction among these entities. The approach is based on expressive semantic representations: information sharing in RDF and content-based publish/subscribe with SPARQL as the subscription language. SPARQL can be used to construct elaborate queries for detecting complex states resulting from receiving events produced by multiple interrelated entities. The notification system should aim at short notification times while simultaneously allowing high throughput of events. We study incremental matching of SPARQL queries on RDF data using Rete algorithm. The results obtained demonstrate that an efficient and fast semantic notification framework can be implemented by representing SPARQL queries and RDF triples as rules and facts in a Rete engine. %@ 978-1-4503-0857-1

@inproceedings{Abdullah:2012:EMS, abstract = {Ubiquitous domains such as smart spaces, location-aware mobile systems, or internet-of-things are characterized by large and volatile sets of heterogeneous and independently behaving entities like devices, services, and other identified objects. This study focuses on efficient implementation of an event processing system to manage interaction among these entities. The approach is based on expressive semantic representations: information sharing in RDF and content-based publish/subscribe with SPARQL as the subscription language. SPARQL can be used to construct elaborate queries for detecting complex states resulting from receiving events produced by multiple interrelated entities. The notification system should aim at short notification times while simultaneously allowing high throughput of events. We study incremental matching of SPARQL queries on RDF data using Rete algorithm. The results obtained demonstrate that an efficient and fast semantic notification framework can be implemented by representing SPARQL queries and RDF triples as rules and facts in a Rete engine.}, acmid = {2245348}, added-at = {2013-07-22T12:51:40.000+0200}, address = {New York, NY, USA}, author = {Abdullah, Haris and Rinne, Mikko and T\"{o}rm\"{a}, Seppo and Nuutila, Esko}, biburl = {https://www.bibsonomy.org/bibtex/2a78a56824889d2b8ab21f302f4ba421c/gron}, booktitle = {Proceedings of the 27th Annual ACM Symposium on Applied Computing}, description = {Efficient matching of SPARQL subscriptions using rete}, doi = {10.1145/2245276.2245348}, interhash = {ae1a5837e95bb0ec32a32122f7f745b5}, intrahash = {a78a56824889d2b8ab21f302f4ba421c}, isbn = {978-1-4503-0857-1}, keywords = {Application Financial Inference Rete Stock}, location = {Trento, Italy}, numpages = {6}, pages = {372--377}, publisher = {ACM}, series = {SAC '12}, timestamp = {2013-07-22T12:51:42.000+0200}, title = {Efficient Matching of SPARQL Subscriptions using Rete}, year = 2012 }