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On the Missing Link Between Frequent Pattern Discovery and Concept Formation

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Inductive Logic Programming (ILP 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4455))

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Abstract

Concept Formation is a unsupervised learning task usually decomposed into the two subtasks of clustering and characterization. This paper presents a novel approach to Concept Formation in First Order Logic (FOL) which adopts a pattern-based approach to clustering and a bias-based approach to characterization. The resulting method extends therefore the levelwise search method for Frequent Pattern Discovery. The FOL fragment chosen is \(\mathcal{AL}\)-log, a hybrid language that merges the description logic \(\mathcal{ALC}\) and the clausal logic Datalog and turns out to be suitable for applications in the context of Ontology Refinement. Indeed the method returns a taxonomy rooted into the concept that occurs in an existing taxonomic ontology and needs to be refined in the light of new knowledge coming from an external data source. Experimental results have been obtained on an \(\mathcal{ALC}\) ontology enriched with Datalog data extracted from the on-line CIA World Fact Book.

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Authors and Affiliations

  1. Dipartimento di Informatica, Università degli Studi di Bari, Via Orabona 4, 70125 Bari, Italy

    Francesca A. Lisi & Floriana Esposito

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  1. Francesca A. Lisi
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  2. Floriana Esposito
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Stephen Muggleton Ramon Otero Alireza Tamaddoni-Nezhad

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Lisi, F.A., Esposito, F. (2007). On the Missing Link Between Frequent Pattern Discovery and Concept Formation. In: Muggleton, S., Otero, R., Tamaddoni-Nezhad, A. (eds) Inductive Logic Programming. ILP 2006. Lecture Notes in Computer Science(), vol 4455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73847-3_30

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  • DOI: https://doi.org/10.1007/978-3-540-73847-3_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73846-6

  • Online ISBN: 978-3-540-73847-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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