Feature-Less End-to-End Nested Term Extraction

Code

• github.com/CooDL/NestedTermExtraction
  OfficialIn paperpytorch★ 8

Abstract

In this paper, we proposed a deep learning-based end-to-end method on the domain specified automatic term extraction (ATE), it considers possible term spans within a fixed length in the sentence and predicts them whether they can be conceptual terms. In comparison with current ATE methods, the model supports nested term extraction and does not crucially need extra (extracted) features. Results show that it can achieve high recall and a comparable precision on term extraction task with inputting segmented raw text.

Tasks

Reproductions