Contrasting Rule-based and Support Vector Machine Approaches to Time Expression Identification in Clinical TempEval

http://www.aclweb.org/anthology/S15-2141
Abstract: We present two approaches to time expression identification, as entered in to SemEval2015 Task 6, Clinical TempEval. The first is a comprehensive rule-based approach that favoured recall, and which achieved the best recall for time expression identification in Clinical TempEval. The second is an SVM-based system built using readily available components, which was able to achieve a competitive F1 in a short development time. We discuss how the two approaches perform relative to each other, and how characteristics of the corpus affect the suitability of different approaches and their outcomes.
 
@inproceedings{TissotEtal2015SemEval,
author    = {Tissot, Hegler  and  Gorrell, Genevieve  and  Roberts, Angus
             and Derczynski, Leon  and  Fabro, Marcos Didonet Del},
title     = {{UFPRSheffield}: Contrasting Rule-based and Support Vector 
             Machine Approaches to Time Expression Identification in Clinical 
             TempEval},
booktitle = {Proceedings of the 9th International Workshop on Semantic 
             Evaluation (SemEval 2015)},
month     = {June},
year      = {2015},
address   = {Denver, Colorado},
publisher = {Association for Computational Linguistics},
pages     = {835--839},
url       = {http://www.aclweb.org/anthology/S15-2141}
}