A Real-World Framework for Translator as Expert Retrieval

  • Navid Rekabsaz
  • Mihai Lupu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8685)

Abstract

This article describes a method and tool to identify expert translators in an on-demand translation service. We start from existing efforts on expert retrieval and factor in additional parameters based on the real-world scenario of the task. The system first identifies topical expertise using an aggregation function over relevance scores of previously translated documents by each translator, and then a learning to rank method to factor in non-topical relevance factors that are part of the decision-making process of the user, such as price and duration of translation. We test the system on a manually created test collection and show that the method is able to effectively support the user in selecting the best translator.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Navid Rekabsaz
    • 1
  • Mihai Lupu
    • 2
  1. 1.Faculty of InformaticsVienna University of TechnologyAustria
  2. 2.Information and Software Engineering GroupVienna University of TechnologyViennaAustria

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