Abstractive text summarization of low-resourced languages using deep learning.

ABSTRACT:

Background

Humans must be able to cope with the huge amounts of information produced by the information technology revolution. As a result, automatic text summarization is being employed in a range of industries to assist individuals in identifying the most important information. For text summarization, two approaches are mainly considered: text summarization by the extractive and abstractive methods. The extractive summarisation approach selects chunks of sentences like source documents, while the abstractive approach can generate a summary based on mined keywords. For low-resourced languages, e.g., Urdu, extractive summarization uses various models and algorithms. However, the study of abstractive summarization in Urdu is still a challenging task. Because there are so many

SUBMITTER: Shafiq N 

PROVIDER: S-EPMC10280265 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature