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Abstract: This article presents the concept of context dependent classification. In context dependent classification of elementary objects, an elementary object is represented by a node in a graph. A node can be identified to belong to a certain node class, if one of the defining (characterizing) contexts for that class can be embedded in the graph properly. Thus, the classification of a node does not only depend on properties of the elementary object itself, but also on properties of its environment.... (Update)
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BibTeX entry: (Update)
@misc{ geibel-learning,
author = "Peter Geibel and Fritz Wysotzki",
title = "Learning Context Dependent and Relational Concepts",
url = "citeseer.ist.psu.edu/412401.html" }
Citations (may not include all citations):1359 Induction of Decision Trees (context) - Quinlan - 1986
77 Protein secondary structure prediction using logic (context) - Muggleton, King et al. - 1992
73 Experiments in Induction (context) - Hunt, Marin et al. - 1966
65 The application of Inductive Logic Programming to finite ele.. - Dolsak, Muggleton - 1992
54 Learning Conjunctive Concepts in Structural Domains (context) - Haussler - 1989
14 Lernfahige Klassifizierungssysteme (context) - Unger, Wysotzki - 1981
11 Background Knowledge and Declarative Bias in Inductive Conce.. (context) - Lavrac, Dzeroski - 1992
10 Knowledge Discovery in a Database of Mutagenic Chemicals (context) - King, Sternberg et al. - 1995
8 Concept Learning by Structured Examples - An Algebraic Appro.. (context) - Wysotzki, Kolbe et al. - 1981
8 Number 558 in Lecture Notes in Mathematics (context) - Weisfeiler, Identification - 1976
4 Begriffslernen fur strukturierte Objekte (context) - Geibel, Schadler et al. - 1995
4 Zum Nachweis der Isomorphie von endlichen Graphen (context) - Tinhofer - 1976
1 Induction of Context Dependent and Relational Concepts (context) - Geibel, Wysotzki - 1995
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