Deep reinforcement and transfer learning for abstractive text summarization: A review

A Alomari, N Idris, AQM Sabri, I Alsmadi - Computer Speech & Language, 2022 - Elsevier
Abstract Automatic Text Summarization (ATS) is an important area in Natural Language
Processing (NLP) with the goal of shortening a long text into a more compact version by …

Automatic text summarization of biomedical text data: a systematic review

A Chaves, C Kesiku, B Garcia-Zapirain - Information, 2022 - mdpi.com
In recent years, the evolution of technology has led to an increase in text data obtained from
many sources. In the biomedical domain, text information has also evidenced this …

Comparison of text preprocessing methods

CP Chai - Natural Language Engineering, 2023 - cambridge.org
Text preprocessing is not only an essential step to prepare the corpus for modeling but also
a key area that directly affects the natural language processing (NLP) application results. For …

A topic modeled unsupervised approach to single document extractive text summarization

R Srivastava, P Singh, KPS Rana, V Kumar - Knowledge-Based Systems, 2022 - Elsevier
Abstract Automatic Text Summarization (ATS) is an essential field in natural language
processing that attempts to condense large text documents so that users can assimilate …

[HTML][HTML] Summarization of scholarly articles using BERT and BiGRU: Deep learning-based extractive approach

S Bano, S Khalid, NM Tairan, H Shah… - Journal of King Saud …, 2023 - Elsevier
Extractive text summarization involves selecting and combining key sentences directly from
the original text, rather than generating new content. While various methods, both statistical …

Bayesian optimization based score fusion of linguistic approaches for improving legal document summarization

D Jain, MD Borah, A Biswas - Knowledge-Based Systems, 2023 - Elsevier
Due to the lengthy and complex nature of legal documents, automatic summarization has
very high applicability in this domain. Recently, several researchers have proposed …

An AI-Resilient Text Rendering Technique for Reading and Skimming Documents

Z Gu, I Arawjo, K Li, JK Kummerfeld… - Proceedings of the CHI …, 2024 - dl.acm.org
Readers find text difficult to consume for many reasons. Summarization can address some of
these difficulties, but introduce others, such as omitting, misrepresenting, or hallucinating …

Natural language processing in finance: A survey

K Du, Y Zhao, R Mao, F **ng, E Cambria - Information Fusion, 2025 - Elsevier
This survey presents an in-depth review of the transformative role of Natural Language
Processing (NLP) in finance, highlighting its impact on ten major financial applications:(1) …

Abstractive text summarization: State of the art, challenges, and improvements

H Shakil, A Farooq, J Kalita - Neurocomputing, 2024 - Elsevier
Specifically focusing on the landscape of abstractive text summarization, as opposed to
extractive techniques, this survey presents a comprehensive overview, delving into state-of …

Extractive multi-document Arabic text summarization using evolutionary multi-objective optimization with K-medoid clustering

R Alqaisi, W Ghanem, A Qaroush - IEEE Access, 2020 - ieeexplore.ieee.org
The increasing usage of the Internet and social networks has produced a significant amount
of online textual data. These online textual data led to information overload and redundancy …