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EGAL: Exploration Guided Active Learning for TCBR

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Case-Based Reasoning. Research and Development (ICCBR 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6176))

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Abstract

The task of building labelled case bases can be approached using active learning (AL), a process which facilitates the labelling of large collections of examples with minimal manual labelling effort. The main challenge in designing AL systems is the development of a selection strategy to choose the most informative examples to manually label. Typical selection strategies use exploitation techniques which attempt to refine uncertain areas of the decision space based on the output of a classifier. Other approaches tend to balance exploitation with exploration, selecting examples from dense and interesting regions of the domain space. In this paper we present a simple but effective exploration-only selection strategy for AL in the textual domain. Our approach is inherently case-based, using only nearest-neighbour-based density and diversity measures. We show how its performance is comparable to the more computationally expensive exploitation-based approaches and that it offers the opportunity to be classifier independent.

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Author information

Authors and Affiliations

  1. Dublin Institute of Technology, Dublin, Ireland

    Rong Hu, Sarah Jane Delany & Brian Mac Namee

Authors
  1. Rong Hu
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  2. Sarah Jane Delany
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  3. Brian Mac Namee
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Editor information

Editors and Affiliations

  1. Institute of Technology, University of Washington, Tacoma, 1900 Commerce Street, Box 358426, 98402, Tacoma, WA, USA

    Isabelle Bichindaritz

  2. Dipartimento di Informatica, Università del Piemonte Orientale, P.O. Box, Alessandria, Italy

    Stefania Montani

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Hu, R., Jane Delany, S., Mac Namee, B. (2010). EGAL: Exploration Guided Active Learning for TCBR. In: Bichindaritz, I., Montani, S. (eds) Case-Based Reasoning. Research and Development. ICCBR 2010. Lecture Notes in Computer Science(), vol 6176. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14274-1_13

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  • DOI: https://doi.org/10.1007/978-3-642-14274-1_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14273-4

  • Online ISBN: 978-3-642-14274-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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