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Second International Conference on Semantics, Knowledge, and Grid (SKG'06)
Embedding the Semantic Knowledge in Convolution Kernels
Guilin, Guangxi, China
November 01-November 03
ISBN: 0-7695-2673-X
ASCII Text
x 
 
Kebin Liu, Fang Li, Ying Han, Lei Liu, "Embedding the Semantic Knowledge in Convolution Kernels," Semantics, Knowledge and Grid, International Conference on, pp. 55, Second International Conference on Semantics, Knowledge, and Grid (SKG'06), 2006.
 
 
BibTex
x
 
@article{ 10.1109/SKG.2006.49,
author = {Kebin Liu and Fang Li and Ying Han and Lei Liu},
title = {Embedding the Semantic Knowledge in Convolution Kernels},
journal ={Semantics, Knowledge and Grid, International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2673-X},
pages = {55},
doi = {http://doi.ieeecomputersociety.org/10.1109/SKG.2006.49},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Semantics, Knowledge and Grid, International Conference on
TI - Embedding the Semantic Knowledge in Convolution Kernels
SN - 0-7695-2673-X
SP
EP
A1 - Kebin Liu,
A1 - Fang Li,
A1 - Ying Han,
A1 - Lei Liu,
PY - 2006
KW - null
VL - 0
JA - Semantics, Knowledge and Grid, International Conference on
ER -
 
Kebin Liu, Shanghai Jiaotong University, China
Fang Li, Shanghai Jiaotong University, China
Ying Han, Shanghai Jiaotong University, China
Lei Liu, Shanghai Jiaotong University, China
Convolution kernels, such as tree kernel and subsequence kernel are useful for natural language processing tasks. However, most of them ignore the semantic knowledge. In order to solve the problem, this paper proposes a new method to embed the semantic knowledge into kernel calculation. The new method has been applied to extract the ORG-affiliation relation from Chinese texts and achieves an average Fmeasure of 82.1%. Comparing with feature-based method and the traditional Word-sequence kernel, it provides significant improvement.
Citation:
Kebin Liu, Fang Li, Ying Han, Lei Liu, "Embedding the Semantic Knowledge in Convolution Kernels," skg, pp.55, Second International Conference on Semantics, Knowledge, and Grid (SKG'06), 2006
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