Techniques of Automatic Term Extraction:Current Sate and Reflections

doi:10.12339/j.issn.1673-8578.2022.01.001

Abstract

Abstract:

This paper overviews the definition, major approaches and the evaluation metrics of the ATE task. For the traditional approaches, we mainly elaborate the measurement of the Unithood and Termhood, using pointwise mutual information, t-value, ti-idf weighting and C/NC-value as examples. For Automatic Term Labelling, we mainly present the sequence labelling modelling. We think the performance of Automatic Term Extraction/Labelling is still not satisfactory from a point of view of real application, and try to offer a few directions of further improvements.

Key words: automatic term extraction, automatic term labelling, unithood, termhood, machine learning

CLC Number:

CHANG Baobao. Techniques of Automatic Term Extraction:Current Sate and Reflections[J]. China Terminology, 2022, 24(1): 3-13.

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