TrigNER: automatically optimized biomedical event trigger recognition on scientific documents.

ABSTRACT:

Background

Cellular events play a central role in the understanding of biological processes and functions, providing insight on both physiological and pathogenesis mechanisms. Automatic extraction of mentions of such events from the literature represents an important contribution to the progress of the biomedical domain, allowing faster updating of existing knowledge. The identification of trigger words indicating an event is a very important step in the event extraction pipeline, since the following task(s) rely on its output. This step presents various complex and unsolved challenges, namely the selection of informative features, the representation of the textual context, and the selection of a specific event type for a trigger word given this context.

Results

We propose T

SUBMITTER: Campos D 

PROVIDER: S-EPMC3896761 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature