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SUMMARY:Towards automated understanding of scientific papers - Maria Liaka
 ta
DTSTART:20090521T110000Z
DTEND:20090521T120000Z
UID:TALK18478@talks.cam.ac.uk
CONTACT:Johanna Geiss
DESCRIPTION:The large number of scientific papers generated\, especially i
 n the life sciences\, makes it a challenge for researchers and resource cu
 rators to extract and evaluate the knowledge contained within them. Automa
 ted text mining methods currently operate mainly on abstracts but scientis
 ts have highlighted the need for the automatic processing of the full text
 . Researchers in information extraction and information retrieval have to 
 be able to recognise areas of interest in papers and scientists have expre
 ssed the need for machine readable summaries. However\, the manual product
 ion of semantic markup in papers is very time consuming and cannot cater f
 or the millions of papers already published.\nWe have produced a tool (SAP
 IENT) and an ontology-based annotation scheme for the annotation of core s
 cientific concepts (CISP) (Goal'\, Motivation'\,Object'\,Hypothesis'\,Back
 ground'\,Model'\,Experiment'\,Method'\,Observation'\,Result'\,`Conclusion'
 ) in research papers. A corpus of 225 papers covering topics in physical c
 hemistry and biochemistry were annotated at the sentence level by 16 exper
 ts using SAPIENT and the CISP-based annotation scheme. Within the SAPIENTA
  project we plan to use this corpus to enable the automatic recognition of
  scientific concepts in papers and generate digital abstracts in both huma
 n and machine readable format. We also aim to enable intelligent querying 
 of the content of scientific papers by exploiting the extra semantic infor
 mation and representing the relevant sections in a first order logic form 
 that reasoners can handle.\n\nBio: Dr Maria Liakata has an Oxford DPhil in
  Computational Linguistics\, on the topic of using Inductive Logic Program
 ming to learn pragmatic knowledge from a corpus (Inducing Domain Theories)
 . Since June 2005 she has been a research associate with the Computational
  Biology group at Aberystwyth University and has worked on interdisciplina
 ry projects\, such as the Robot Scientist\, involving the automation and f
 ormalisation of science. 
LOCATION:SW01\, Computer Laboratory
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