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New Approach for Clustering Relational Data Based on Relationship and Attribute Information

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Abstract

A wide range of the database systems in use today are based on the relational model. As a consequence, more information used by those systems has been stored in multi relational object types. However, most of the traditional machine learning algorithms have not been originally proposed to handle this type of data. Aiming to propose better ways of handling the relational particularities of the data, this paper proposes a new relational clustering method based on relationship and attribute information. In our method, attributes have weights associated with their importance between the object types. An empirical analysis is performed in order to evaluate the effectiveness of the proposed method, comparing with two traditional methods for relational clustering. Three relational databases were used in the experiments.

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Author information

Authors and Affiliations

  1. Informatics and Applied Mathematics Department, Federal University of Rio Grande do Norte, Natal, RN, Brazil, 59072-970

    João Carlos Xavier-Júnior & Anne M. P. Canuto

  2. Computing and Automation Engineering Department, Federal University of Rio Grande do Norte, Natal, RN, Brazil, 59078-900

    Luiz M. G. Gonçalves & Luiz A. H. G. de Oliveira

Authors
  1. João Carlos Xavier-Júnior

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  2. Anne M. P. Canuto

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  3. Luiz M. G. Gonçalves

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  4. Luiz A. H. G. de Oliveira

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Editor information

Editors and Affiliations

  1. Neuro Heuristic Research Group, University of Lausanne, 1015, Lausanne, Switzerland

    Alessandro E. P. Villa

  2. Department of Informatics, Nicolaus Copernicus University, 87-100, Toruń, Poland

    Włodzisław Duch

  3. Center for Complex Systems Studies, Kalamazoo College, 49006, Kalamazoo, MI, USA

    Péter Érdi

  4. Dipartimento di Informatica e Scienze dell’Informazione, Università di Genova, 16146, Genoa, Italy

    Francesco Masulli

  5. Institut für Neuroinformatik, Universität Ulm, 89069, Ulm, Germany

    Günther Palm

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© 2012 Springer-Verlag Berlin Heidelberg

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Xavier-Júnior, J.C., Canuto, A.M.P., Gonçalves, L.M.G., de Oliveira, L.A.H.G. (2012). New Approach for Clustering Relational Data Based on Relationship and Attribute Information. In: Villa, A.E.P., Duch, W., Érdi, P., Masulli, F., Palm, G. (eds) Artificial Neural Networks and Machine Learning – ICANN 2012. ICANN 2012. Lecture Notes in Computer Science, vol 7553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33266-1_56

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JPY 5719
Price includes VAT (Japan)
  • Available as PDF
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Price includes VAT (Japan)
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