Autonomous Decentralized Kernel Cache Architecture for Multi Ontology Based Information Extraction on Microsoft Windows

Ontology Based Information Extraction (OBIE) is being adopted in various domains in order to improve the system's precision and recall. Though use of multiple ontologies in different semantic based Information Extraction systems helps to improve the system extraction accuracy but the performance of system degrades significantly. This paper proposes autonomous decentralized kernel cache architecture to improve the query time for OBIE systems that utilize multiple ontologies. In order to minimize performance bottlenecks we propose caching most frequently used relations of the ontologies in the autonomous and decentralized kernel cache in order to reduce the query time against different semantic queries. Results show performance improvement for different queries made on YAGO2s and DBpedia ontologies using the proposed kernel based Onto-Cache.