Learning Logical Descriptions for Document Understanding: A Rough SetsBased Approach
 Emmanuelle Martienne,
 Mohamed Quafafou
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Abstract
Inductive learning systems in a logical framework are prone to difficulties when dealing with huge amount of information. In particular, the learning cost is greatly increased, and it becomes difficult to find descriptions of concepts in a reasonable time. In this paper, we present a learning approach based on Rough Set Theory, and more especially on its basic notion of concept approximation. In accordance with RST, a learning process is splitted into three steps, namely (1) partitioning of knowledge, (2) approximation of the target concept, and finally (3) induction of a logical description of this concept. The second step of approximation reduces the volume of the learning data, by computing wellchosen portions of the background knowledge which represent approximations of the concept to learn. Then, only one of these portions is used during the induction of the description, which allows for reducing the learning cost. In the first part of this paper, we report how RST’s basic notions namely indiscernibility, as well as lower and upper approximations of a concept have been adapted in order to cope with a logical framework. In the remainder of the paper, some empirical results obtained with a concrete implementation of the approach, i.e., the EAGLE system, are given. These results show the relevance of the approach, in terms of learning cost gain, on a learning problem related to the document understanding.
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 Title
 Learning Logical Descriptions for Document Understanding: A Rough SetsBased Approach
 Book Title
 Rough Sets and Current Trends in Computing
 Book Subtitle
 First International Conference, RSCTC’98 Warsaw, Poland, June 22–26, 1998 Proceedings
 Pages
 pp 202209
 Copyright
 1998
 DOI
 10.1007/3540691154_28
 Print ISBN
 9783540646556
 Online ISBN
 9783540691150
 Series Title
 Lecture Notes in Computer Science
 Series Volume
 1424
 Series ISSN
 03029743
 Publisher
 Springer Berlin Heidelberg
 Copyright Holder
 SpringerVerlag Berlin Heidelberg
 Additional Links
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 Industry Sectors
 eBook Packages
 Editors

 Lech Polkowski ^{(1)}
 Andrzej Skowron ^{(2)}
 Editor Affiliations

 1. Institute of Mathematics, Warsaw University of Technology
 2. Institute of Mathematics, Warsaw University
 Authors

 Emmanuelle Martienne ^{(5)}
 Mohamed Quafafou ^{(5)}
 Author Affiliations

 5. Institut de Recherche en Informatique de Nantes (IRIN), 2, rue de la Houssinire, B.P. 92208, 44322, Nantes cedex 3
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