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Classifier combination techniques applied to coreference resolution (2009)
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| Venue: | In Proceedings of the NAACL-HLT2009 Student Research Workshop and Doctoral Consortium |
| Citations: | 3 - 0 self |
BibTeX
@INPROCEEDINGS{Vemulapalli09classifiercombination,
author = {Smita Vemulapalli and Xiaoqiang Luo and John F. Pitrelli and Imed Zitouni},
title = {Classifier combination techniques applied to coreference resolution},
booktitle = {In Proceedings of the NAACL-HLT2009 Student Research Workshop and Doctoral Consortium},
year = {2009},
pages = {1--6}
}
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Abstract
This paper examines the applicability of classifier combination approaches such as bagging and boosting for coreference resolution. To the best of our knowledge, this is the first effort that utilizes such techniques for coreference resolution. In this paper, we provide experimental evidence which indicates that the accuracy of the coreference engine can potentially be increased by use of bagging and boosting methods, without any additional features or training data. We implement and evaluate combination techniques at the mention, entity and document level, and also address issues like entity alignment, that are specific to coreference resolution. 1
