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HRDB2015

Abstract:

We present ExB Medical Text Miner – a text mining pipeline for processing biomedical documents. This application employs state- of-the-art Named Entity Recognition, using linguistic features and word embeddings in a fully-connected second-order Conditional Random Field model, as well as a novel two-stage Relation Extraction module that first detects entity-level relations using a Support Vector Classifier, then iden- tifies document-level relations by measuring their relevance according to a document topic classification model.

Type: Inproceedings

Author: Hänig, C. and Remus, R. and Demchik, V. and Bordag, S.
Title: ExB Medical Text Miner
Booktitle: Proceedings of the Fifth BioCreative Challenge Evaluation Workshop
Year: 2015
Pages:202-207
Address:Seville, Spain
@INPROCEEDINGS{HRDB2015,
AUTHOR = {Hänig, C. and Remus, R. and Demchik, V. and Bordag, S.},
TITLE = {ExB Medical Text Miner},
BOOKTITLE = {Proceedings of the Fifth BioCreative Challenge Evaluation Workshop},
YEAR = {2015},
PAGES = {202-207},
ADDRESS = {Seville, Spain}
}