Evaluating Noise Reduction Strategies for Terminology Extraction

نویسندگان

  • Johannes Schäfer
  • Ina Rösiger
  • Ulrich Heid
  • Michael Dorna
چکیده

We present work on the task of reducing noise in nominal terminology extraction. Based on a comparative evaluation of statistical measures aimed at capturing domain specificity, we propose strategies to increase the typically quite low accuracy of classical hybrid nominal multi-word term extraction. Our experiments on a set of German do-it-yourself instruction texts show that using linguistic filters that determine the right span of the MWE before applying a suitable combination of statistical measures improves results.

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تاریخ انتشار 2015