Conceptual Knowledge Discovery - a Human-Centered Approach.
Journal of Applied Artificial Intelligence (AAI), 17(3):281-301, 2003.
Joachim Hereth, Gerd Stumme, Rudolf Wille und Uta Wille.
[doi]
[Kurzfassung]
[BibTeX]
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. We dicuss how the
management system TOSCANA for conceptual information systems
supports CKDD, and illustrate it by two applications in database
marketing and flight movement analysis. Finally, we present a
new tool for conceptual deviation discovery, Chianti.
Attribute Exploration on the Web.
In: P. Cellier, F. Distel und B. Ganter
(Herausgeber):
Contributions to the 11th International Conference on Formal Concept Analysis, Seiten 19-34.
2013.
Robert Jäschke und Sebastian Rudolph.
[doi]
[Kurzfassung]
[BibTeX]
We propose an approach for supporting attribute exploration by web information retrieval, in particular by posing appropriate queries to search engines, crowd sourcing systems, and the linked open data cloud. We discuss underlying general assumptions for this to work and the degree to which these can be taken for granted.