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Machine Learning

, Volume 24, Issue 2, pp 95–122 | Cite as

A lattice conceptual clustering system and its application to browsing retrieval

  • Claudio Carpineto
  • Giovanni Romano
Article

Abstract

The theory of concept (or Galois) lattices provides a simple and formal approach to conceptual clustering. In this paper we present GALOIS, a system that automates and applies this theory. The algorithm utilized by GALOIS to build a concept lattice is incremental and efficient, each update being done in time at most quadratic in the number of objects in the lattice. Also, the algorithm may incorporate background information into the lattice, and through clustering, extend the scope of the theory. The application we present is concerned with information retrieval via browsing, for which we argue that concept lattices may represent major support structures. We describe a prototype user interface for browsing through the concept lattice of a document-term relation, possibly enriched with a thesaurus of terms. An experimental evaluation of the system performed on a medium-sized bibliographic database shows good retrieval performance and a significant improvement after the introduction of background knowledge.

Keywords

conceptual clustering incremental learning concept lattices browsing information retrieval 

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Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • Claudio Carpineto
    • 1
  • Giovanni Romano
    • 1
  1. 1.Fondazione Ugo BordoniRomeItaly

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