DLIA99 Discussion summary:

II: Table recognition and interpretation

Discussion Chair: Taku Tokuyasu

Our group, consisting of sixteen people from seven countries, about equally divided between academic, industrial, and government institutions, discussed the problem of "table recognition and interpretation".  While it is impossible to do justice to the variety of ideas that were presented, I attempt to extract some themes below.  We hope that this will be the start of ongoing discussions on these and related topics.  For an informal transcript of the discussion, click here (I am indebted to Amit Mukherjee for permission to copy his notes).
 

What is a table?

The answer to this question is often application-driven.  A person interested only in the financial data in the third column of row two of an ascii table within an email message may view the problem quite differently from someone who wants to capture details of  a complex presentational layout or design a general schema for table metadata.  The various points of view can be organized as follows: The possibility of recursion is a common theme in all of the above representations.  While there may be a general understanding of the elements of these representations, the community does not appear to have settled on a standard description of any of them.  Perhaps this indicates that we do not understand the problem well enough yet.

Performance evaluation

Careful study of the performance of implemented systems is an important way to measure progress.  Simply defining what it means to evaluate performance can clarify the goals of research.  Here again it is important to note that the objective function (i.e. performance metric) will be application-specific.  A system which can consistently identify the "third column in the second row" of a table may be all that is needed in one kind of application, and woefully inadequate in another.

In order to start large-scale evaluations, the existence of databases of empirical data and the corresponding ground truth is highly desirable.   This presents a bit of a chicken-and-egg problem, since in order to generate the ground-truth data, we first have to decide what constitutes "truth" in this context.
 

General questions and comments

 

Participants

[Note: The following names are in the order in which they appeared on the original list (with additions), in an attempt to preserve the spatial layout!]

Hiroshi Shimodaira
JAIST
sim@jaist.ac.jp

Andreas Moser
DFKI
moser@dfki.de

Thomas Bayer
Siemens
thomas.bayer@kst.siemens.de

Lyse Robadey
University of Fribourg, CH
lyse.robadey@unifr.ch

Amit Mukerjee
IIT Kanpur
amit@iitk.ac.in

Koichi Kise
Osaka Prefecture University
kise@cs.osakafu-u.ac.jp

Steve Dennis
U.S. DOD
sjdenni@afterlife.ncsc.mil

Ihsin Phillips
Seattle University
yun@seattleu.edu

Robert Haralick
University of WA
haralick@ee.washington.edu

Jianying Hu
Bell Labs
jianhu@bell-labs.com

Ram Kashi
Bell Labs
ramanuja@bell-labs.com

Oliver Hitz
University of Fribourg
oliver.hitz@unifr.ch

Markus Junker
DFKI
markus.junker@dfki.de

Steve Simske
Hewlett-Packard
Steven_Simske@hp.com

Laurent Najman
OCE
laurent.najman@ocegr.fr

Ching Suen
Concordia University
suen@cenparmi.concordia.ca

Taku Tokuyasu
UC Berkeley
tokuyasu@cs.berkeley.edu

Thomas Breuel
Xerox Palo Alto Research Center
tbreuel@parc.xerox.com

Marcel Worring
University of Amsterdam
worring@wins.uva.nl
 


Taku Tokuyasu, discussion chair.
Last modified 11/3/99