Ontology Matching is among the most used techniques for hetrogeniety resolution; however, eﬀective ontology matching is a computationally intensive operation requiring optimized matching algorithms to be executed over candidate ontologies. SPHeRe is a performance-based initiative that improves ontology matching performance by exploiting parallelism over multicore Desktops and Cloud Platforms.
- Implement parallelism wherever needed from ontology loading till bridge ontology dilivery.
- A thread-safe ontology model for multithreaded environment.
- Mechanism to reduce memory footprint during matching.
- Better computational resource utilization.
- Combination of ontology matching techniques to generate accurate mappings among heterogeneous ontologies.