Statistical Parsing for Information Extraction from Scientific Articles
This event took place on Wednesday 17 November 2004 at 12:45
Dr. Ted Briscoe University of Cambridge Computer Laboratory
I'll describe the states-of-the-art in statistical parsing and information extraction (IE), present the RASP (Robust Accurate Statistical Parsing) System for English, and outline our project with FlyBase, Cambridge to develop an IE system capable of supporting efficient curation of functional genomic information from the fruit fly literature.
I'll argue that IE from the full text of scientific articles requires full statistical parsing, both to reliably locate useful information and to integrate the IE system effectively with domain resources, and that migration to the semantic web/grid creates exciting opportunities, both for generic integration of IE into curation and experimentation and efficient porting of IE to new domains.
This event took place on Wednesday 17 November 2004 at 12:45
Dr. Ted Briscoe University of Cambridge Computer Laboratory
I'll describe the states-of-the-art in statistical parsing and information extraction (IE), present the RASP (Robust Accurate Statistical Parsing) System for English, and outline our project with FlyBase, Cambridge to develop an IE system capable of supporting efficient curation of functional genomic information from the fruit fly literature.
I'll argue that IE from the full text of scientific articles requires full statistical parsing, both to reliably locate useful information and to integrate the IE system effectively with domain resources, and that migration to the semantic web/grid creates exciting opportunities, both for generic integration of IE into curation and experimentation and efficient porting of IE to new domains.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Multimedia and Information Systems is...
We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.
Visit the MMIS website
List all Multimedia and Information Systems Projects
Check out these Hot Multimedia and Information Systems Technologies:
List all Multimedia and Information Systems Technologies
