Evaluating the Reliability and Interaction of Recursively Used Feature Classes for Terminology Extraction

Abstract

Feature design and selection is a crucial aspect when treating terminology extraction as a machine learning classification problem. We designed feature classes which characterize different properties of terms, and propose a new feature class for components of term candidates. By using random forests, we infer optimal features which are later used to build… (More)

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