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Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1
Automatic Entity Relation Extraction Based on Maximum Entropy
Jinan, China
October 16-October 18
ISBN: 0-7695-2528-8
ASCII Text
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Suxiang Zhang, Juan Wen, Xiaojie Wang, Lei Li, "Automatic Entity Relation Extraction Based on Maximum Entropy," Intelligent Systems Design and Applications, International Conference on, vol. 1, pp. 540-544, Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1, 2006.
 
 
BibTex
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@article{ 10.1109/ISDA.2006.115,
author = {Suxiang Zhang and Juan Wen and Xiaojie Wang and Lei Li},
title = {Automatic Entity Relation Extraction Based on Maximum Entropy},
journal ={Intelligent Systems Design and Applications, International Conference on},
volume = {1},
year = {2006},
isbn = {0-7695-2528-8},
pages = {540-544},
doi = {http://doi.ieeecomputersociety.org/10.1109/ISDA.2006.115},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Intelligent Systems Design and Applications, International Conference on
TI - Automatic Entity Relation Extraction Based on Maximum Entropy
SN - 0-7695-2528-8
SP540
EP544
A1 - Suxiang Zhang,
A1 - Juan Wen,
A1 - Xiaojie Wang,
A1 - Lei Li,
PY - 2006
KW - Maximum Entropy
KW - feature selection
KW - entity relation extraction and evaluation
VL - 1
JA - Intelligent Systems Design and Applications, International Conference on
ER -
 
Suxiang Zhang, Beijing University of Posts and Telecommunications, China
Juan Wen, Beijing University of Posts and Telecommunications, China
Xiaojie Wang, Beijing University of Posts and Telecommunications, China
Lei Li, Beijing University of Posts and Telecommunications, China
Entity Relation Extraction (RE) is an very important research domain in Information Extraction, we can regard RE as a classification problem in this paper, RE is still original study field in Chinese language now, Maximum Entropy (ME)-based machine learning is the first time to be used to extract entity relations between named entities from Chinese texts, Thirteen features have been designed for entity relation extraction, which includes Morphology, grammar and semantic feature. The system architecture for RE has been constructed. Experiment shows that the performance is promising. So it is useful for ME-based machine learning to solve RE problem.
Index Terms:
Maximum Entropy, feature selection, entity relation extraction and evaluation
Citation:
Suxiang Zhang, Juan Wen, Xiaojie Wang, Lei Li, "Automatic Entity Relation Extraction Based on Maximum Entropy," isda, vol. 1, pp.540-544, Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1, 2006
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