An optimized hybrid deep learning model based on word embeddings and statistical features for extractive summarization

Wazery, Yaser M.; Saleh, Marwa E.; Ali, Abdelmgeid A.

doi:10.1016/j.jksuci.2023.101614

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

An optimized hybrid deep learning model based on word embeddings and statistical features for extractive summarization

Cited by 3 publications

References 29 publications

A systematic literature review of deep learning-based text summarization: Techniques, input representation, training strategies, mechanisms, datasets, evaluation, and challenges

A systematic literature review of deep learning-based text summarization: Techniques, input representation, training strategies, mechanisms, datasets, evaluation, and challenges

Enhancing Abstractive Text Summarization with Proximal Policy Optimization

Review on Text Summarization using Clustering and Machine Learning-Deep Learning Models

Contact Info

Product

Resources

About