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International Conference on Intelligent Systems Design and Applications

ISDA 2016: Intelligent Systems Design and Applications pp 279–288Cite as

Bayesian Networks for Identifying Semantic Relations in a Never-Ending Learning System

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 557))

Abstract

A new paradigm of Machine Learning named Never-Ending Learning has been proposed through a system known as NELL (Never-Ending Language Learning). The major idea of this system is to learn to read the web better each day and to store the gathered knowledge in a knowledge base (KB), continually and incrementally. This paper proposes a new method that can help NELL populating its own KB using Bayesian Networks (BN). More specifically, we use facts (knowledge) already stored in NELL’s KB as input for a BN learning algorithm named VOMOS (Variable Ordering Multiple Offspring Sampling) by aiming at representing the acquired knowledge by NELL system. In addition, we propose to use the BN induced by VOMOS for identifying new semantic relations to be added to NELL’s KB, expanding thus its initial ontology.

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Acknowledgments

The authors acknowledge the Brazilian Institutional Program – PIBIC/FAPEMIG/UFSJ – by the scholarship granted through document no. 002/2014/PROPE to develop this research and the Univ. Lyon - UJM-Saint-Etienne (CNRS,Laboratoire Hubert Curien) in France for the support.

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Authors and Affiliations

  1. DComp/UFSJ – Department of Computer Science, Federal University of São João del-Rei, São João del-Rei, Minas Gerais, Brazil

    Edimilson Batista dos Santos & Massilon Lourenço Fernandes

  2. DC/UFSCar – Computer Department, Federal University of São Carlos, São Carlos, São Paulo, Brazil

    Estevam R. Hruschka Jr.

  3. Univ. Lyon, UJM-Saint-Etienne, CNRS, Laboratoire Hubert Curien UMR 5516, 42023, Saint Etienne, France

    Maísa Cristina Duarte

Authors
  1. Edimilson Batista dos Santos
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  2. Massilon Lourenço Fernandes
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  3. Estevam R. Hruschka Jr.
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  4. Maísa Cristina Duarte
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Corresponding author

Correspondence to Maísa Cristina Duarte .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Instituto Superior de Engenharia do Port, Porto, Portugal

    Ana Maria Madureira

  2. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  3. Polytechnic Institute of Porto, Felgueiras, Portugal

    Dorabela Gamboa

  4. Campus of Gualtar, University of Minho, Braga, Portugal

    Paulo Novais

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dos Santos, E.B., Fernandes, M.L., Hruschka, E.R., Duarte, M.C. (2017). Bayesian Networks for Identifying Semantic Relations in a Never-Ending Learning System. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_28

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  • DOI: https://doi.org/10.1007/978-3-319-53480-0_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53479-4

  • Online ISBN: 978-3-319-53480-0

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