Big-BirdPegasus based Abstractive Multi-Document Summarization

Registration ID: IJNRD_190489

Published ID: IJNRD2304226

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P..Spandana valli , N.usha satwika , S. Vijay swaroop , V.V. Leela prasad , B. venkata lakshmi

We are introducing a new method of multi-document summarization[2] that utilizes our Big Bird Pegasus transformers (BBPT) in conjunction with Maximal Marginal Relevance (MMR). Our approach generates candidate breviloquent sentences and then uses MMR to select the most relevant and diverse sentences for inclusion in the arbitrary. In this research, we propose a method for multi-document summarization using Big Bird Pegasus[3] along with MMR. We import the dataset directly from the ski-learn library and split it into 70% for training and 30% for testing the model. Our proposed model achieved an accuracy of 80% when tested on the same dataset by extracting 30% of the information.

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P..Spandana valli, N.usha satwika, S. Vijay swaroop, V.V. Leela prasad, & B. venkata lakshmi (April-2023). Big-BirdPegasus based Abstractive Multi-Document Summarization. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(4), c210-c218. https://ijnrd.org/papers/IJNRD2304226.pdf

Volume 8 Issue 4, April-2023

Pages : c210-c218

Paper Reg. ID: IJNRD_190489

Published Paper Id: IJNRD2304226

Downloads: 000121984

Research Area: Computer Engineering 

Country: visakhapatnam, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2304226.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304226

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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