DocumentCode :
3023907
Title :
A model for detecting and merging vertically spanned table cells in plain text documents
Author :
Long, Vanessa ; Dale, Robert ; Cassidy, Steve
Author_Institution :
Centre for Language Technol., Macquarie Univ., Sydney, NSW, Australia
fYear :
2005
fDate :
29 Aug.-1 Sept. 2005
Firstpage :
1242
Abstract :
A spanned cell in a table is a single, complete unit that physically occupies multiple columns and/or multiple rows. Spanned cells are common in tables, and they are a significant cause of error in the extraction of tables from free text documents. In this paper, we present a model for the detection and merging of vertically spanned cells for tables presented in plain text documents. Our model and algorithm are based purely on the layout features of the tables, and they require no semantic understanding of the documents. When tested on the 98 tables appearing in 40 randomly selected documents from a corpus of company announcements from the Australian Stock Exchange (ASX), our algorithm achieves an accuracy of 86.79% in detecting and merging vertically spanned cells.
Keywords :
text analysis; document semantic understanding; free text documents; plain text documents; vertically spanned table cell detection; vertically spanned table cell merging; Australia; Data mining; IEEE news; Merging; Robustness; Stock markets; Terminology; Testing; Text analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on
ISSN :
1520-5263
Print_ISBN :
0-7695-2420-6
Type :
conf
DOI :
10.1109/ICDAR.2005.21
Filename :
1575741
Link To Document :
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