research product . 2021

Learning Robust Representations for Low-resource Information Extraction

Zhou, Yichao;
Open Access English
  • Published: 01 Jan 2021
  • Publisher: eScholarship, University of California
  • Country: United States
Abstract
Information extraction (IE) plays a significant role in automating the knowledge acquisition process from unstructured or semi-structured textual sources. Named entity recognition and relation extraction are the major tasks of IE discussed in this thesis. Traditional IE systems rely on high-quality datasets of large scale to learn the semantic and structural relationship between the observations and labels while such datasets are rare especially in the area of low-resource language processing (e.g. figurative language processing and clinical narrative curation). This leads to the problems of inadequate supervision and model over-fitting. In this thesis, we work ...
Subjects
free text keywords: Computer science, Information Extraction, Natural Language Processing, Text Mining
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