A Parallel Environment Designing for OWL Thinking

A huge volume of information available today is in the form of images and searching the wanted images is very difficult and highly time-consuming. The search may take longer periods as the search volume on the internet is very huge and also the relevance of extracted images is still not up to the mark. The technologies like ontology and languages like OWL help us to tag the images that describe the semantic of the images. Hence, it helps in faster searching of the wanted images. Also, another challenge with OWL and Semantic web is the speed in which one can derive the relationships between various objects extracted from the images. The challenge is to extract the semantic from the images more efficiently using a parallel approach. In this paper, we explore the different techniques for generating semantic knowledge using parallel approaches like the T-box approach, merge classification, extract concept for matching ontology. We propose an enhanced method to speed-up the computation by combining T-box and merge classification techniques.