Nov 14

We developed a tool for scalable language processing for our customer Lingit using Amazon’s Elastic Mapreduce.

More details:

Contact us if you need help with Hadoop/Elastic Mapreduce.

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2 Responses to “Atbrox Customer Case Study – Scalable Language Processing with Elastic Mapreduce (Hadoop)”

  1. Øystein Nytrø Says:

    Referring to the customer case, I would guess that n-gram postprocessing and subsequent model-building are the most complex, and depending on n, computationally intensive tasks. Was that
    done locally afterwards, or did you manage to distribute that also?

    — Øystein N.

  2. amund Says:

    the scope of this project was the creation of n-gram and not the processing afterwards (except some filtering).

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