Semantic searches for extracting similarities in a content management system

Abstract

Recent content management systems have restricted means for organizing and inferring documents although much of an organization's knowledge can be created in text repositories. In the Semantic Web search emergence, inferring and understanding can be deal by ontology-based semantic mark-up and metadata management. Whilst in the educational domain, learning objects are a fundamental resource. Literally, Content Management Systems and repositories have restricted the means for organising and understanding the captured semantic relationships between the learning objects and other stored documents. To cater this situation, we propose the application of metametadata as a useful semantic based approach to address similarities in a domain to gather definite requirements. This paper focuses on the existing approaches for describing semantic relationships in Content Management Systems and how metametadata capture the pedagogic information which can be applied to enhance the semantic information stored within such a Content Management Systems or repository. It is understood that there is still lacking approaches to address similarities in a domain that meets certain requirements but the progress for the ongoing research in the area is active and shows potential advancement.