karl bühler digital

Home > Book Series > Proceedings > Contribution

Publication details

Publisher: Springer

Place: Berlin

Year: 2004

Pages: 94-108

Series: Lecture Notes in Computer Science

ISBN (Hardback): 9783540223924

Full citation:

Bernhard Ganter, Sergei O. Kuznetsov, "Concept-based data mining with scaled labeled graphs", in: Conceptual structures at work, Berlin, Springer, 2004

Abstract

Graphs with labeled vertices and edges play an important role in various applications, including chemistry. A model of learning from positive and negative examples, naturally described in terms of Formal Concept Analysis (FCA), is used here to generate hypotheses about biological activity of chemical compounds. A standard FCA technique is used to reduce labeled graphs to object-attribute representation. The major challenge is the construction of the context, which can involve ten thousands attributes. The method is tested against a standard dataset from an ongoing international competition called Predictive Toxicology Challenge (PTC).

Publication details

Publisher: Springer

Place: Berlin

Year: 2004

Pages: 94-108

Series: Lecture Notes in Computer Science

ISBN (Hardback): 9783540223924

Full citation:

Bernhard Ganter, Sergei O. Kuznetsov, "Concept-based data mining with scaled labeled graphs", in: Conceptual structures at work, Berlin, Springer, 2004