Auto-Enhancement of Text Summarization by using Extractive Method
Author(s):
POTNURI GAYATRI , G MOHITH SATYA GOVIND, K. RAJAN, M. DURGA PRASAD
Keywords:
Text summarization, Extractive method, Natural language processing(NLP),Auto- Enhancement, text.
Abstract
The purpose of this undertaking of auto-enhancement of text summarization the usage of extractive methods in NLP entails automatically enhancing the fine of summaries generated by means of extracting the most important sentences or phrases from a textual content. Extractive summarization involves identifying and extracting the most applicable sentences or phrases from a larger textual content, in place of producing new text. NLP techniques consisting of Named Entity reputation (NER), part-of-Speech (POS) tagging, and semantic analysis can be used to identify critical sentences and phrases based totally on their relevance to the overall that means of the textual content. To beautify the satisfactory of an extractive summary, one approach is to use system mastering algorithms to discover the maximum important capabilities of the textual content, together with keywords, named entities, and sentiment. those features can then be used to weight the importance of person sentences or phrases, ensuring that the precis captures the most vital records in the authentic textual content. average, auto-enhancement of text summarization the use of extractive techniques in NLP has the capability to noticeably enhance the efficiency and accuracy of summarization responsibilities, particularly in fields which include information media and educational studies wherein summarization is regularly required to quick and correctly bring essential facts.
Article Details
Unique Paper ID: 159027

Publication Volume & Issue: Volume 9, Issue 11

Page(s): 151 - 159
Article Preview & Download


Share This Article

Conference Alert

NCSST-2023

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2023

SWEC- Management

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2023

Latest Publication

Go To Issue



Call For Paper

Volume 10 Issue 1

Last Date for paper submitting for March Issue is 25 June 2023

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:6351679790
Email: editor@ijirt.org
Website: ijirt.org

Policies

Important Links

Browse Rsearch papers