Details of Grant 

EPSRC Reference:	GR/T22902/01
Title:	ABRAXAS: Automating Ontology Learning for the Semantic Web
Principal Investigator:	Wilks, Professor Y
Other Investigators:	Ciravegna, Professor F Guthrie, Dr L
Researcher Co-Investigators:	Professor C Brewster
Project Partners:	Active Navigation Ltd
Department:	Computer Science
Organisation:	University of Sheffield
Scheme:	Standard Research (Pre-FEC)
Starts:	01 October 2004	Ends:	31 January 2007	Value (£):	164,614
EPSRC Research Topic Classifications:	Artificial Intelligence Information & Knowledge Mgmt
EPSRC Industrial Sector Classifications:	Information Technologies
Related Grants:
Panel History:
Summary on Grant Application Form
One of the acknowledged road blocks to the development of Artificial Intelligence, the Semantic Web and Knowledge Management is knowledge acquisition. This project will develop computational methods to construct knowledge representations (ontologies) automatically from texts. We will analyse how knowledge i presented in texts and identify that which is computationally interpretable and extractable. We will construct appropriate collection of data for our experiments, including text corpora and ontologies. Using machine learning methods, we will collect different sets of textual patterns, each associated with a particular ontologic relation (e.g. is-a, part-of, is-located-in). The data sparsity issue (i.e. the relative absence of explicit contexts; we will deal with by identifying and integrating secondary knowledge sources, such manuals, encyclopedias, and possibly the Internet itself. The novelty of this project lies in the use of machine learning to acquire the textual patterns, the application of Adaptive Information Extraction to this task, and the integration with external knowledge sources. A comprehensive evaluation methodology will be developed to allow the assessment of the automated output of our methodologies according to different parameters. The outcome c this research will enable ontologies to be constructed from scratch, or extended far more easily and speedily than is at present possible.
Key Findings
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Potential use in non-academic contexts
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Impacts
Description This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk Summary Date Materialised
Sectors submitted by the Researcher
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Project URL:
Further Information:
Organisation Website:	http://www.shef.ac.uk