Name
Title | ||
|---|---|---|
Structured learning for spatial information extraction from biomedical text: bacteria biotopes. |
Abstract | ||
|---|---|---|
We aim to automatically extract species names of bacteria and their locations from webpages. This task is important for exploiting the vast amount of biological knowledge which is expressed in diverse natural language texts and putting this knowledge in databases for easy access by biologists. The task is challenging and the previous results are far below an acceptable level of performance, particularly for extraction of localization relationships. Therefore, we aim to design a new system for such extractions, using the framework of structured machine learning techniques. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1186/s12859-015-0542-z | BMC Bioinformatics |
Keywords | Field | DocType |
biomedical research,bioinformatics,microarrays,algorithms | Spatial analysis,Information retrieval,Web page,Computer science,Structured prediction,Biomedical text mining,Natural language,Bioinformatics | Journal |
Volume | Issue | ISSN |
16 | 1 | 1471-2105 |
Citations | PageRank | References |
9 | 0.66 | 35 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Parisa Kordjamshidi | 1 | 143 | 18.52 |
| Dan Roth | 2 | 7735 | 695.19 |
| Marie-Francine Moens | 3 | 1750 | 139.27 |