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Output details

11 - Computer Science and Informatics

University of Manchester

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Output 45 of 179 in the submission
Article title

Boosting automatic event extraction from the literature using domain adaptation and coreference resolution

Type
D - Journal article
Title of journal
Bioinformatics
Article number
-
Volume number
28
Issue number
13
First page of article
1759
ISSN of journal
1460-2059
Year of publication
2012
URL
-
Number of additional authors
2
Additional information

<24> Extracting complex relations (events) from text is important for advanced fine-grained semantic search. Challenges for event extraction systems are generalization to new domains and event types, and coreference resolution (linking event entities across text). The novelty here is incorporation of these abilities in EventMine, making it the best performing system in extracting events from biomedical text (evidence: comparative evaluation in community shared tasks (BioNLP)). EventMine underpins event extraction for Europe PubMed Central text-mining based search facilities (having extracted 80m events from 2.5m documents), and two search services offered by the National Centre for Text Mining.

Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
7
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-