A multi-paradigm fuzzy aggregation of domain ontology and media assets on the semantic web framework

The semantic web defined as an extension to the present web allows interoperable data representation and expression of meaningful relationship between data objects. Its popularity has been supported by its deduction capabilities, that being one of the limitations of current web. In a semantic web framework, an ontology enables the description of conceptual structures for knowledge sharing, processing, and facilitates interpretation of meaningful relationship between objects. Here a metadata structure describes media assets, and concepts are retrieved based on author preferences. These concepts are mental structures which are closely coupled by the fuzziness of human language. We propose an inference method supported by fuzzy proximity to process associations between media objects and human perceptions. A fuzzy weight factor is introduced for establishing dynamic association between human perceptions and media assets in a domain.