Abstract
Recently, extraction systems have also used link grammar to identify interactions between proteins. In this chapter, the authors present a fully automated system to extract biomolecular events from biomedical abstracts. By semantically classifying each sentence to the class type of the event and then using high-coverage rules, BioEve extracts the participants of that event. The chapter explains in detail different classification approaches, and event extraction using a dependency parse tree of the sentence is explained here. It describes experiments with classification approaches, event extraction, and evaluation results for the BioNLP'09 shared task 1.
Original language | English (US) |
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Title of host publication | Biological Knowledge Discovery Handbook |
Subtitle of host publication | Preprocessing, Mining and Postprocessing of Biological Data |
Publisher | Wiley |
Pages | 943-967 |
Number of pages | 25 |
ISBN (Electronic) | 9781118617151 |
ISBN (Print) | 9781118853726 |
DOIs | |
State | Published - 2014 |
ASJC Scopus subject areas
- Computer Science(all)