Investigating the Core Technologies of the Semantic Web

The Semantic Web research group explores a variety of important topics that underpin the Semantic Web vision, combining it with Social/People Web (including Web 2.0) and services computing where appropriate.

  • Spatio-temporal-thematic processing: We are investigating new analytical query operators that exploit the graph-centric nature of RDF data, and we are also investigating efficient techniques for storing and querying spatial and temporal data.
  • Semantic analytics: We have developed specification and extraction of meaningful paths between different entities using our research in path queries on Semantic Web data. Given a graph and entities present in it,it gives the capability to extract the connection between the entities.
  • Knowledge Extraction from biomedical text:
    • Identification and extraction of complex entities
    • Classification of complex entities
    • Extraction of Relationships between entities and representation as semi-structured data (RDF)
    • Hypothesis formulation/discovery over RDF data
  • Knowledge extraction from social text
  • Making sense of informal text: We are applying statistical and Natural Language processing techniques to the analysis of casual data originating from social software such as blogs, chat, discussions in social networks etc. The goal is to effectively glean semantics from such data in order to support applications that use the data and the underlying structure from which they originate. Examples of some applications include sentiment analysis and targeted advertising.
  • Graphical Formulation of Complex Queries and Processing