| dc.contributor.author |
Từ, Minh Phương |
|
| dc.date.accessioned |
2011-04-20T08:56:38Z |
|
| dc.date.available |
2011-04-20T08:56:38Z |
|
| dc.date.issued |
2003 |
|
| dc.identifier.citation |
K.-Y. Whang, J. Jeon, K. Shim, J. Srivatava (Eds.): PAKDD 2003, LNAI 2637, pp. 148–158, 2003. © Springer-Verlag Berlin Heidelberg 2003 |
vi |
| dc.identifier.uri |
http://hdl.handle.net/123456789/1119 |
|
| dc.description.abstract |
We present a method for automatic extraction of protein interactions
from scientific abstracts by combing machine learning and knowledge-based
strategies. This method uses sample sentences, which are parsed by a link
grammar parser, to learn extraction rules automatically. By incorporating
heuristic rules based on morphological clues and domain specific knowledge,
this method can remove the interactions that are not between proteins and
improve the performance of extraction process. We present experimental results
for a test set of MEDLINE abstracts. The results are encouraging and
demonstrate the feasibility of our method to perform accurate extraction
without need of manual rule building. |
vi |
| dc.description.sponsorship |
Quỹ Giáo dục Cao học Hàn Quốc (The Korea Foundation for Advanced Studies) & Trung tâm Hỗ trợ Nghiên cứu Châu Á, ĐHQGHN (Asia Research Center, VNU) |
vi |
| dc.language.iso |
en |
vi |
| dc.publisher |
Springer-Verlag Berlin Heidelberg |
vi |
| dc.title |
Learning Rules to Extract Protein Interactions from Biomedical Text |
vi |
| dc.type |
Working Paper |
vi |