DocumentCode
2144644
Title
Table Content Understanding in SmartFIX
Author
Deckert, S. ; Seidler, Benjamin ; Ebbecke, Markus ; Gillmann, Michael
Author_Institution
Insiders Technol. GmbH, Kaiserslautern, Germany
fYear
2011
fDate
18-21 Sept. 2011
Firstpage
488
Lastpage
492
Abstract
The analysis of table structures and the retrieval of table contents is widely agreed to be a difficult challenge in the area of document analysis systems. Instead of extracting the layout of tables, we are interested in understanding their content. In this paper, we present and discuss the smartFIX approach to table recognition and content extraction. Rather than relying on layout features only, we recognize tables by taking into account the presence and semantics of data entities that we expect to find contained in a table. The relationship of a document, including a table, to a specific business process aids in shaping helpful knowledge and expectations about the table´s content. smartFIX is a commercial document analysis system complying with the complete bandwidth of industrial requirements. Therefore, smartFIX must locate the tables and extract its business process relevant information with high reliability.
Keywords
business data processing; content management; document handling; information retrieval; pattern recognition; business process aids; content extraction; data entities; document analysis systems; document capturing systems; layout features; semantics; smartFIX; table content understanding; table contents retrieval; table recognition; table structures analysis; Business; Databases; Layout; Measurement; Semantics; Text analysis; document analysis; smartFIX; table analysis; table content extraction; table recognition; table understanding;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location
Beijing
ISSN
1520-5363
Print_ISBN
978-1-4577-1350-7
Electronic_ISBN
1520-5363
Type
conf
DOI
10.1109/ICDAR.2011.104
Filename
6065359
Link To Document