Name
Title | ||
|---|---|---|
BioEve: bio-molecular event extraction from text using semantic classification and dependency parsing |
Abstract | ||
|---|---|---|
In this paper, we present BioEve a fully automated event extraction system for bio-medical text. It first semantically classifies each sentence to the class type of the event mentioned in the sentence, and then using high coverage hand-crafted rules, it extracts the participants of that event. We participated in Task 1 of BioNLP 2009 Shared task, and the final evaluation results are described here. Our experimentation with different approaches to classify a sentence to bio-interaction classes are also shared. |
Year | Venue | Keywords |
|---|---|---|
2009 | BioNLP@HLT-NAACL (Shared Task) | automated event extraction system,final evaluation result,bio-medical text,class type,dependency parsing,high coverage,bio-molecular event extraction,shared task,different approach,hand-crafted rule,semantic classification |
Field | DocType | Citations |
Information retrieval,Computer science,Dependency grammar,Biomedical text mining,Natural language processing,Artificial intelligence,Sentence | Conference | 5 |
PageRank | References | Authors |
0.48 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Syed Toufeeq Ahmed | 1 | 42 | 5.27 |
| Radhika Nair | 2 | 5 | 1.16 |
| Chintan Patel | 3 | 385 | 37.44 |
| Hasan Davulcu | 4 | 584 | 86.85 |