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Integrating Declarative Knowledge in Hierarchical Clustering Tasks

  • Luis Talavera
  • Javier Béjar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1642)

Abstract

The capability of making use of existing prior knowledge is an important challenge for Knowledge Discovery tasks. As an unsupervised learning task, clustering appears to be one of the tasks that more benefits might obtain from prior knowledge. In this paper, we propose a method for providing declarative prior knowledge to a hierarchical clustering system stressing the interactive component. Preliminary results suggest that declarative knowledge is a powerful bias in order to improve the quality of clustering in domains were the internal biases of the system are inappropriate or there is not enough evidence in data and that it can lead the system to build more comprehensible clusterings.

Keywords

Prior Knowledge Background Knowledge Cluster Process Cluster System Inductive Logic Programming 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Luis Talavera
    • 1
  • Javier Béjar
    • 1
  1. 1.Departament de Llenguatges i Sistemes InformàticsUniversitat Politècnica de CatalunyaBarcelonaSpain

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