Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)

A Comparative Study on Statistical Classification Methods in Relation Extraction

Authors
Zhang Xiaofeng, Gao Zhiqiang, Gui Yaocheng
Corresponding Author
Zhang Xiaofeng
Available Online November 2013.
DOI
https://doi.org/10.2991/icmt-13.2013.21How to use a DOI?
Keywords
Relation Extraction, Named Entity Recognition, Statistical Classification
Abstract
This paper is a comparative study of statistical classification approaches in relation extraction and classification. The focus is on multiclass classification, not on sequence labeling. Five methods are evaluated, including naive Bayes (NB), decision tree (DT), k-nearest neighbor (kNN), support vector machine (SVM) and sparse network of Winnow (SNoW). Using DT on Roth and Yih data set, the best precision and recall are achieved on both tasks of named entity recognition (NER) and relation extraction (RE). SNoW is not so good as DT, but it performs better than the other approaches. SVM performs better on precision and worse on recall. In contrast, the simplest methods NB and kNN has relative poor performance but they are not sensitive to learning tasks and classes.
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Proceedings
3rd International Conference on Multimedia Technology(ICMT-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
November 2013
ISBN
978-90-78677-89-5
ISSN
1951-6851
DOI
https://doi.org/10.2991/icmt-13.2013.21How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Zhang Xiaofeng
AU  - Gao Zhiqiang
AU  - Gui Yaocheng
PY  - 2013/11
DA  - 2013/11
TI  - A Comparative Study on Statistical Classification Methods in Relation Extraction
BT  - 3rd International Conference on Multimedia Technology(ICMT-13)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmt-13.2013.21
DO  - https://doi.org/10.2991/icmt-13.2013.21
ID  - Xiaofeng2013/11
ER  -