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Algorithms for Robust Knowledge Extraction in Learning Environments

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Intelligent Tutoring Systems (ITS 2010)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 6095))

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Abstract

This paper presents preliminary results on a generalizability study that was carried out to evaluate the robustness of a knowledge extraction algorithm.

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References

  1. de la Chica, S., Ahmad, F., Martin, J.H., Sumner, T.: Pedagogically useful extractive summaries for science education. In: Proceedings of the 22nd International Conference on Computational Linguistics, vol. 1, pp. 177–184. Association for Computational Linguistics (2008)

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© 2010 Springer-Verlag Berlin Heidelberg

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Okoye, I., Maull, K., Sumner, T. (2010). Algorithms for Robust Knowledge Extraction in Learning Environments. In: Aleven, V., Kay, J., Mostow, J. (eds) Intelligent Tutoring Systems. ITS 2010. Lecture Notes in Computer Science, vol 6095. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13437-1_33

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  • DOI: https://doi.org/10.1007/978-3-642-13437-1_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13436-4

  • Online ISBN: 978-3-642-13437-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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