Advancements in Automatic Text Summarization using Natural Language Processing
Journal Title: International Journal of Innovations in Science and Technology - Year 2025, Vol 7, Issue 2
Abstract
With the rapid expansion of data across various domains, the need for automated text summarization has become increasingly crucial. Given the overwhelming volume of textual and numerical data, effective summarization techniques are required to extract key information while preserving content integrity. Text summarization has been a subject of research for decades, with various approaches developed using natural language processing (NLP) and a combination of different algorithms. This paper is an SLR-type essay presenting the existing text summarization techniques and their evaluation. It covers the basic concepts behind extractive and abstractive summarization and how deep learning models could serve as a boost in the performance of summarization. The study goes on to investigate the present use of text summarization in different areas and investigatesthe various methodologies applied in this area. A total of twenty-four carefully selected research articles were being analyzed to identify key trends, challenges and limitations regarding text summarization techniques. Itproposes a number of open research challenges with insight concerning possible future directions in text summarization
Authors and Affiliations
Roha Irfan, Rabia Tehseen, Anam Mustaqeem, Ramsha Saeed, Usman Aamer, Jawad Hassan
Keywords
Related Articles
- EP ID EP769796
- DOI -
- Views 5
- Downloads 0
Assessing the IoT Acceptance at Public Sector Universities of Sindh, Pakistan
The Internet of Things (IoT) technology blends the real world and digital life, ensuring seamless integration for accomplishing tasks to make life easier. Analysts often get lost in the deep technical details of IoT, but...
A Computational Studyof Ichthyofaunal Diversity of River Kabul
Mcclelland initiated the scientific study of the fish species of the River Kabul in 1842, and many researchers have continued this work since then. The primary goal of these studies has been to do a computational study...
Hybrid Intrusion Detection System Based on Optimal Feature Selection and Evolutionary Algorithm for Wired Networks
The field of cybersecurity encounters ongoing difficulties in identifying and preventing attacks in networks, and the pervasive threat of cyberattacks demands continual advancements in intrusion detection sys...
SmartTutor: Ensuring User Privacy in Distance Education with AI-Driven Tutoring and Multilingual Knowledge Retrieval
Today, in this digital era, getting access to all such information is essential for education and learning. Indeed, most of the existing content is useful if utilized appropriately or in conjunction with developed solu...
Smart Power Management with Small Cells: A Path to Sustainable Data Connectivity
The rising demand for energy-efficient networks capable of supporting high-speed data traffic poses a critical challenge for network operators. This study addresses this issue by proposing a power control strategy that...