Template-Type: ReDIF-Article 1.0
Author-Name:Roha  Irfan, Rabia  Tehseen, Anam  Mustaqeem, Ramsha  Saeed,Usman  Aamer,Jawad Hassan
Author-Email:rabia.tehseen@ucp.edu.pk
Author-Workplace-Name:Department of Computer Science, University of Central Punjab, Lahore, Pakistan, Department of Software Engineering, University of Central Punjab, Lahore, Pakistan
Title:Advancements in Automatic Text Summarization using Natural Language Processing
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.
Keywords:Natural   language   processing   (NLP),   Text   summarization,   Automatic   text Summarization, Extractive Method (EXT), Abstractive Method (ABS), Deep learning)
Journal:International Journal of Innovations in Science and Technology
Pages:1145-1460
Volume:7
Issue:2
Year:2025
Month:June
File-URL:https://journal.50sea.com/index.php/IJIST/article/view/1405/1947
File-Format: Application/pdf
File-URL:https://journal.50sea.com/index.php/IJIST/article/view/1405
File-Format: text/html
Handle: RePEc:abq:IJIST:v:7:y:2025:i:2:p:1145-1460