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Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 1
A Case-Based Reasoning Approach for Invoice Structure Extraction
Curitiba, Parana, Brazil
September 23-September 26
ISBN: 0-7695-2822-8
ASCII Text
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H. Hamza, Y. Bela?, A. Bela?, "A Case-Based Reasoning Approach for Invoice Structure Extraction," Document Analysis and Recognition, International Conference on, vol. 1, pp. 327-331, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 1, 2007.
 
 
BibTex
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@article{ 10.1109/ICDAR.2007.3,
author = {H. Hamza and Y. Bela? and A. Bela?},
title = {A Case-Based Reasoning Approach for Invoice Structure Extraction},
journal ={Document Analysis and Recognition, International Conference on},
volume = {1},
year = {2007},
issn = {1520-5363},
pages = {327-331},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.2007.3},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Document Analysis and Recognition, International Conference on
TI - A Case-Based Reasoning Approach for Invoice Structure Extraction
SN - 1520-5363
SP327
EP331
A1 - H. Hamza,
A1 - Y. Bela?,
A1 - A. Bela?,
PY - 2007
VL - 1
JA - Document Analysis and Recognition, International Conference on
ER -
 
H. Hamza, LORIA, University Nancy 2. France
Y. Bela?, LORIA, University Nancy 2. France
A. Bela?, LORIA, University Nancy 2. France
This paper shows the use of case-based reasoning (CBR) for invoice structure extraction and analysis. This method, called CBR-DIA (CBR for Document Invoice Analysis), is adaptive and does not need any previous training. It analyses a document by retrieving and analysing similar documents or elements of documents (cases) stored in a database. The retrieval step is performed thanks to graph comparison techniques like graph probing and edit dis- tance. The analysis step is done thanks to the information found in the nearest retrieved cases. Applied on 950 in- voices, CBR-DIA reaches a recognition rate of 85.29% for documents of known classes and 76.33% for documents of unknown classes.
Citation:
H. Hamza, Y. Bela?, A. Bela?, "A Case-Based Reasoning Approach for Invoice Structure Extraction," icdar, vol. 1, pp.327-331, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 1, 2007
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