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CONCEPTUAL KNOWLEDGE DISCOVERY--A HUMAN-CENTERED APPROACH 

Authors: Joachim Hereth Correia a;  Gerd Stumme b;  Rudolf Wille a; Uta Wille c
Affiliations:   a Technische Universitaumlt Darmstadt, Fachbereich Mathematik, Darmstadt, Germany.
b Institut fuumlr Angewandte Informatik und Formale Beschreibungsverfahren (AIFB), Universitaumlt Karlsruhe (TH), Karlsruhe, Germany.
c Jelmoli AG, E-Commerce & Database Marketing, Zuumlrich, Switzerland.
DOI: 10.1080/713827122
Publication Frequency: 10 issues per year
Published in: journal Applied Artificial Intelligence, Volume 17, Issue 3 March 2003 , pages 281 - 302
Formats available: PDF (English)
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Abstract

In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) as it is developing in the field of Conceptual Knowledge Processing. Conceptual Knowledge Processing is based on the mathematical theory of Formal Concept Analysis, which has become a successful theory for data analysis during the last two decades. CKDD aims to support a human-centered process of discovering knowledge from data by visualizing and analyzing the conceptual structure of the data. Basic to the philosophy of CKDD is the idea that only the human analyst is able to make meaningful decisions, and that the analysis tools should not oversimplify the data, but help the analyst to deal with the complex situation. We discuss how the management system TOSCANA for conceptual information systems is supporting those goals of CKDD, and illustrate it by two applications in database marketing and flight movement analysis. Finally, we present a new tool for conceptual deviation discovery, C HIANTI .
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