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COALA – Correlation-Aware Active Learning of Link Specifications

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Part of the book series:Lecture Notes in Computer Science ((LNISA,volume 7882))

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Abstract

Link Discovery plays a central role in the creation of knowledge bases that abide by the five Linked Data principles. Over the last years, several active learning approaches have been developed and used to facilitate the supervised learning of link specifications. Yet so far, these approaches have not taken the correlation between unlabeled examples into account when requiring labels from their user. In this paper, we address exactly this drawback by presenting the concept of the correlation-aware active learning of link specifications. We then present two generic approaches that implement this concept. The first approach is based on graph clustering and can make use of intra-class correlation. The second relies on the activation-spreading paradigm and can make use of both intra- and inter-class correlations. We evaluate the accuracy of these approaches and compare them against a state-of-the-art link specification learning approach in ten different settings. Our results show that our approaches outperform the state of the art by leading to specifications with higher F-scores.

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Author information

Authors and Affiliations

  1. Department of Computer Science, AKSW Research Group, University of Leipzig, Germany

    Axel-Cyrille Ngonga Ngomo, Klaus Lyko & Victor Christen

Authors
  1. Axel-Cyrille Ngonga Ngomo
  2. Klaus Lyko
  3. Victor Christen

Editor information

Editors and Affiliations

  1. CITEC, University of Bielefeld, 33615, Bielefeld, Germany

    Philipp Cimiano

  2. Universidad Politécnica de Madrid, 28660, Boadilla del Monte, Spain

    Oscar Corcho

  3. National Research Council, 00136, Rome, Italy

    Valentina Presutti

  4. Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands

    Laura Hollink

  5. Technische Universität Dresden, 01069, Dresden, Germany

    Sebastian Rudolph

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© 2013 Springer-Verlag Berlin Heidelberg

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Cite this paper

Ngomo, AC.N., Lyko, K., Christen, V. (2013). COALA – Correlation-Aware Active Learning of Link Specifications. In: Cimiano, P., Corcho, O., Presutti, V., Hollink, L., Rudolph, S. (eds) The Semantic Web: Semantics and Big Data. ESWC 2013. Lecture Notes in Computer Science, vol 7882. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38288-8_30

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