MPEG-7 Based Multimedia Information Integration through Instance Matching

Integration of heterogeneous information and acquisition of diverse knowledge from independent media is getting researchers´ attention at a rapid pace. Heterogeneous contents turn out to become sharable objects. In this connection, MPEG-7 standard evolves for containing structured data and knowledge source. The content is described by structured XML data, which is convertible into rich semantic resource description framework (RDF). However, diverse media creators are creating similar types of contents by the way of different instantiation. Therefore, integrating the contents or acquiring sharable knowledge is a formidable task. In this paper, we propose a method to focus on the integration of the resources or instances of MPEG-7 to produce a sharable integrated knowledge base. We use a resource matching, widely called as instance matching in the field of semantic technology to align available MPEG-7 resources. In this regard, we use our scalable ontology alignment algorithm to integrate related resources in cross media. Our preliminary experiments show the strength of our proposed instance matching algorithm.