Multimedia Web Ontology Language

Multimedia Web Ontology Language (MOWL) has been designed to facilitate semantic interactions with multimedia contents. It supports perceptual modeling of concepts using expected media properties. While the reasoning in traditional ontology languages, e.g. Web Ontology Language (OWL), is based on Description Logics, MOWL supports a probabilistic reasoning framework based on Bayesian Network.

History

W3C forum has undertaken the initiative of standardizing the ontology representation for web-based applications. The Web Ontology Language (OWL), standardized in 2004 after maturing through XML(S), RDF(S) and DAML+OIL is a result of that effort. Ontology in OWL (and some of its predecessor languages) has been successfully used in establishing semantics of text in specific application contexts.

The concepts and properties in these traditional ontology languages are expressed as text, making an ontology readily usable for semantic analysis of textual documents. Semantic processing of media data calls for perceptual modeling of domain concepts with their media properties. Such modeling was first proposed in the Ph.D. Thesis by Hiranmay Ghosh (Electrical Engineering Department, IIT Delhi, 2002) in the form of Knowledge Description Language (KDL). With the standardization of OWL by W3C, KDL was merged with OWL to form Multimedia Web Ontology Language (MOWL). Several students have taken the work further to implement research prototypes of retrieval systems and ontology learning.

Key Features

Syntactically, MOWL is an extension of OWL. These extensions enable

MOWL is accompanied with reasoning tools that support

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