Name
Title | ||
|---|---|---|
Complex biological event extraction from full text using signatures of linguistic and semantic features |
Abstract | ||
|---|---|---|
Building on technical advances from the BioNLP 2009 Shared Task Challenge, the 2011 challenge sets forth to generalize techniques to other complex biological event extraction tasks. In this paper, we present the implementation and evaluation of a signature-based machine-learning technique to predict events from full texts of infectious disease documents. Specifically, our approach uses novel signatures composed of traditional linguistic features and semantic knowledge to predict event triggers and their candidate arguments. Using a leave-one out analysis, we report the contribution of linguistic and shallow semantic features in the trigger prediction and candidate argument extraction. Lastly, we examine evaluations and posit causes for errors in our complex biological event extraction. |
Year | Venue | Keywords |
|---|---|---|
2011 | BioNLP@ACL (Shared Task) | full text,novel signature,shared task challenge,complex biological event extraction,candidate argument extraction,infectious disease document,traditional linguistic feature,semantic knowledge,candidate argument,shallow semantic feature,infectious disease,machine learning |
Field | DocType | Citations |
Semantic memory,Computer science,Computational linguistics,Biomedical text mining,Natural language processing,Artificial intelligence,Linguistics,Machine learning | Conference | 6 |
PageRank | References | Authors |
0.45 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liam R. McGrath | 1 | 8 | 1.19 |
| Kelly Domico | 2 | 17 | 2.20 |
| Courtney D. Corley | 3 | 67 | 10.51 |
| Bobbie-Jo M. Webb-Robertson | 4 | 25 | 1.98 |