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Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'06)
HTML Pattern Generator--Automatic Data Extraction from Web Pages
Timisoara, Romania
September 26-September 29
ISBN: 0-7695-2740-X
ASCII Text
x 
 
Mirel Cosulschi, Adrian Giurca, Bogdan Udrescu, Nicolae Constantinescu, Mihai Gabroveanu, "HTML Pattern Generator--Automatic Data Extraction from Web Pages," Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on, pp. 75-78, Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'06), 2006.
 
 
BibTex
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@article{ 10.1109/SYNASC.2006.43,
author = {Mirel Cosulschi and Adrian Giurca and Bogdan Udrescu and Nicolae Constantinescu and Mihai Gabroveanu},
title = {HTML Pattern Generator--Automatic Data Extraction from Web Pages},
journal ={Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on},
volume = {0},
year = {2006},
isbn = {0-7695-2740-X},
pages = {75-78},
doi = {http://doi.ieeecomputersociety.org/10.1109/SYNASC.2006.43},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on
TI - HTML Pattern Generator--Automatic Data Extraction from Web Pages
SN - 0-7695-2740-X
SP75
EP78
A1 - Mirel Cosulschi,
A1 - Adrian Giurca,
A1 - Bogdan Udrescu,
A1 - Nicolae Constantinescu,
A1 - Mihai Gabroveanu,
PY - 2006
KW - null
VL - 0
JA - Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on
ER -
 
Mirel Cosulschi, University of Craiova, Romania
Adrian Giurca, Brandenburg Technical University Cottbus, Germany
Bogdan Udrescu, University of Craiova, Romania
Nicolae Constantinescu, University of Craiova, Romania
Mihai Gabroveanu, University of Craiova, Romania
Existing methods of information extraction from HTML documents include manual approach, supervised learning and automatic techniques. The manual method has high precision and recall values but it is difficult to apply it for large number of pages. Supervised learning involves human interaction to create positive and negative samples. Automatic techniques benefit from less human effort but they are not highly reliable regarding the information retrieved.
Citation:
Mirel Cosulschi, Adrian Giurca, Bogdan Udrescu, Nicolae Constantinescu, Mihai Gabroveanu, "HTML Pattern Generator--Automatic Data Extraction from Web Pages," synasc, pp.75-78, Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'06), 2006
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