Abstract Proceedings of IESMDT - 2021
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EXTRACTIVE BASED NEWS TEXT SUMMARIZING USING NLP
The great development of newsgroups has made accurate access to large amounts of information difficult. Managing large amounts of data requires expert and effective strategies. One such technique is a text summary, which presents information in a condensed form. It would be useful for any user to have access to a large amount of information in a short period of time while improving the news. This article uses data from English newsgroups and Tamil newsgroups to automate news summaries by calculating content location. The proposed work was done using a modified text order calculation that depends on the word repetition rule. The proposed approach makes the word vectors the center and the similarities between the two word the edge between them, which is the ribbon between them. Term repetition assigns different weights to different terms in the sentence, while the standard cosine approximation respects the two in comparison. The vector is sparsely supplied and divided into groups according to why the sentences in the set are indistinguishable and the sentences in different groups reflect their uniqueness.
News Text Summarizing, NLP
17/09/2021
48
IESMDT46
IMPORTANT DAYS
Paper Submission Last Date
October 20th, 2024
Notification of Acceptance
November 7th, 2024
Camera Ready Paper Submission & Author's Registration
November 1st, 2024
Date of Conference
November 15th, 2024
Publication
January 30th, 2025