Open AccessIdentification and Effective Summary Extraction with Deduplication of Data in News Articles
Author(s) -
Rajat Bodankar,
Mayuri S. Waghmare
Publication year - 2020
Publication title -
international journal of scientific research in science, engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-1990
pISSN - 2394-4099
DOI - 10.32628/ijsrset207620
Subject(s) - computer science , data deduplication , identification (biology) , process (computing) , information retrieval , data extraction , information extraction , odds , world wide web , data mining , data science , database , machine learning , programming language , botany , logistic regression , medline , political science , law , biology
Text summary, which is the most prominent application for data pressure, is provided for natural language processing. Content rundown is a process for the summary of the unique archive measurement by reducing the number of vital data from a uniquely reported report. In less time, a need emerges that the development of information increases greatly on the World Wide Web or on desktops of customers so that the multi-document overview is the best way of summarising it in less time. This paper presents an examination of existing procedures with the odds of stressing the need for an intelligent multi-document resumer.