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SUMMARY:BrainNet: Using Brain (and Corpus) Data to Investigate Conceptual 
 Knowledge  - Massimo Poesio\, University of Essex
DTSTART:20131101T120000Z
DTEND:20131101T130000Z
UID:TALK47973@talks.cam.ac.uk
CONTACT:Tamara Polajnar
DESCRIPTION:Existing electronic repositories of lexical and commonsense kn
 owledge such as ConceptNet\, Cyc\, FrameNet\, and especially WordNet (Fell
 baum\,1998)\, have had a dramatic and positive impact on Artificial Intel
 ligence\n(AI) and Human Language Technology (HLT) research\, making it pos
 sible to carry out the first large-scale semantic analyses of text and so
 me simple forms of inference. Nowadays there are few semantic interpretati
 on systems that do not use WordNet. However\, the widespread application o
 f these resources has also highlighted their limitations. One example of p
 roblem often mentioned in the literature is that the taxonomy structure of
  WordNet\, which plays a crucial role e.g.\, in the calculation of lexical
  distance metrics\, is based in part on scientific taxonomies for specific
  domains (e.g.\, animals\, plants)\, in part on linguistic intuitions.\n\n
 The hypothesis underlying the BrainNet project is that the dramatic advanc
 es in our knowledge of concepts arising from interdisciplinary research of
  the last thirty years pave the way to the development of a lexical resour
 ce of a novel type that may overcome the limits just discussed: an electro
 nic dictionary that directly mirrors the mental lexicon\, modelled on the 
 basis of recordings of brain activity using contemporary neuroimaging tech
 niques (EEG\, MEG and fMRI). The goal\nof the BrainNet project is to trans
 late cutting-edge theories and methods from cognitive psychology\, computa
 tional linguistics\, and cognitive neuroscience into a new model for lexic
 al-semantic representation and organization.\n\nJoint work with Andrew And
 erson\, Brian Murphy\, Yuqiao Gu\, Marco Baroni\, and Yuan Tao.\n
LOCATION:FW26\, Computer Laboratory
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