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International Workshop on Challenges in Web Information Retrieval and Integration
Postal Address Detection fromWeb Documents
Tokyo, Japan
April 08-April 09
ISBN: 0-7695-2414-1
ASCII Text
x 
 
Lin Can, Zhang Qian, Meng Xiaofeng, Liu Wenyin, "Postal Address Detection fromWeb Documents," Challenges in Web Information Retrieval and Integration, International Workshop on, pp. 40-45, International Workshop on Challenges in Web Information Retrieval and Integration, 2005.
 
 
BibTex
x
 
@article{ 10.1109/WIRI.2005.28,
author = {Lin Can and Zhang Qian and Meng Xiaofeng and Liu Wenyin},
title = {Postal Address Detection fromWeb Documents},
journal ={Challenges in Web Information Retrieval and Integration, International Workshop on},
volume = {0},
year = {2005},
isbn = {0-7695-2414-1},
pages = {40-45},
doi = {http://doi.ieeecomputersociety.org/10.1109/WIRI.2005.28},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Challenges in Web Information Retrieval and Integration, International Workshop on
TI - Postal Address Detection fromWeb Documents
SN - 0-7695-2414-1
SP40
EP45
A1 - Lin Can,
A1 - Zhang Qian,
A1 - Meng Xiaofeng,
A1 - Liu Wenyin,
PY - 2005
KW - null
VL - 0
JA - Challenges in Web Information Retrieval and Integration, International Workshop on
ER -
 
Lin Can, School of Information, Renmin University Beijing, PRC
Zhang Qian, School of Information, Renmin University Beijing, PRC
Meng Xiaofeng, School of Information, Renmin University Beijing, PRC
Liu Wenyin, Department of Computer Science, City University of Hong Kong Tat Chee Avenue, Hong Kong SAR, PRC

An approach to postal address detection from webpages is proposed. The webpages are first segmented into text blocks based on their visual similarity. The text content in each block undergoes the recognition process, which employs a syntactic approach. The grammars of almost all possible patterns of postal addresses are built for this purpose. The results of our preliminary experiments on 44 webpages with 56 true addresses show that our approach can detect the postal addresses with a high precision (89.3%) and a low false alarms rate (3.8%).

Citation:
Lin Can, Zhang Qian, Meng Xiaofeng, Liu Wenyin, "Postal Address Detection fromWeb Documents," wiri, pp.40-45, International Workshop on Challenges in Web Information Retrieval and Integration, 2005
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