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SUMMARY: LION-LBD: Literature-Based Discovery for Cancer Biology - Simon B
 aker\, LTL
DTSTART:20181011T100000Z
DTEND:20181011T110000Z
UID:TALK112234@talks.cam.ac.uk
CONTACT:Edoardo Maria Ponti
DESCRIPTION:*Abstract*: The overwhelming size and rapid growth of the biom
 edical literature make it impossible for scientists to read all studies re
 lated to their work\, potentially leading to missed connections and wasted
  time and resources.\n\nWe have developed LION-LBD\, a literature-based di
 scovery system that helps cancer researchers to make new discoveries from 
 already published text. The system supports the idea of hypothesis generat
 ion and testing with the aid of text mining. The system is built with a pa
 rticular focus on the molecular biology of cancer using state-of-the-art n
 atural language processing\, including named entity recognition and ground
 ing to domain ontologies covering a wide range of entity types and a novel
  approach to detecting references to the hallmarks of cancer in text.\n\n*
 Bio*: Simon Baker is a research associate (postdoc) at the Language Techno
 logy Lab (LTL). He also collaborates with the Natural Language and Informa
 tion Processing (NLIP) group at the Computer Laboratory. His current resea
 rch interests include: information extraction\, text mining\, and related 
 applications such as automatic Literature-based Discovery (LBD). He works 
 largely in the biomedical domain.\n
LOCATION:Board Room\, 1st floor\, English Faculty Building (Sidgwick site)
 \, 9 West Road\, Cambridge
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