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Reproducibility of the Neural Vector Space Model via Docker

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Part of the Communications in Computer and Information Science book series (CCIS,volume 1177)

Abstract

In this work we describe how Docker images can be used to enhance the reproducibility of Neural IR models. We report our results reproducing the Vector Space Neural Model (NVSM) and we release a CPU-based and a GPU-based Docker image. Finally, we present some insights about reproducing Neural IR models.

The full paper has been originally presented at the OSIRRC@SIGIR workshop [3].

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  • DOI: 10.1007/978-3-030-39905-4_1
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Notes

  1. 1.

    https://www.docker.com/.

  2. 2.

    https://github.com/usnistgov/trec_eval.

References

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Correspondence to Nicola Ferro , Stefano Marchesin , Alberto Purpura or Gianmaria Silvello .

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Ferro, N., Marchesin, S., Purpura, A., Silvello, G. (2020). Reproducibility of the Neural Vector Space Model via Docker. In: Ceci, M., Ferilli, S., Poggi, A. (eds) Digital Libraries: The Era of Big Data and Data Science. IRCDL 2020. Communications in Computer and Information Science, vol 1177. Springer, Cham. https://doi.org/10.1007/978-3-030-39905-4_1

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  • DOI: https://doi.org/10.1007/978-3-030-39905-4_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-39904-7

  • Online ISBN: 978-3-030-39905-4

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