The goal of the Semantic Web initiative is to create a universal medium for information exchange by encoding machine-processable meaning (or semantics) within documents across the World Wide Web. The machine readable descriptions enabled by such Semantic Web Technologies as: XML, RDF and OWL permit content managers, authors to add meaning to document content thus enabling automated information gathering and research by computers. Thus a Semantic Information System based on Semantic Web technology is an interconnected system that is used in the acquisition, storage, manipulation, management, control, display, interchange, or reception of semantically enriched information. The aim of the system is to provide information when and where required, which is complete and the correct level of detail, so that it is useful for some purpose.

Language Engineering (LE) is the applied component of computational linguistics which focuses on the practical outcome of modelling human language use. Applications of LE can include: terminology databases, information retrieval systems, machine translation, multilingual knowledge acquisition, voice recognition, information extraction systems amongst others. Knowledge Acquisition via Semantic Authoring and Ontology Authoring is vital to the growth and success of the Semantic Web. More importantly, the majority of web documents contain either free or partially structured text. Human Language Technology (HLT) will play a crucial role to overcome the knowledge acquisition bottleneck by providing support for the Ontology Authoring and semi-automatic Semantic Annotation.

The current research goals and research activities of SMILE with respect to above include but are not limited to:

  • Architectural development with respect to Semantic Information Systems i.e Social Semantic Software, Social Semantic Desktop(s), Ontology Lifecycle creation and maintenance systems in compliance with emerging standardization efforts. Architecture can include: the development of ontologies, connectors and connector infrastructure, APIs, metadata exchange formats, security concepts, architectural middleware prototyping and subsequent validation and quality assessment.
  • Tools development for collaborative Semi-automatic Semantic Annotation of unstructured data within the context of Semantic Desktops and Semantic Wikis
  • User centric collaborative authoring environments to enable the creation, population and maintenance of ontologies and subsequent support for the ontology lifecycle.
  • Ontology driven content creation and reference management for domain specific publications
  • Tools development for Semantic Annotation of Multimedia.
  • Ontology based Information Extraction the purpose of which is to extract meaningful units of text and consequent.



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