A Data-driven Latent Semantic Analysis for Automatic Text Summarization using LDA Topic Modelling-Reference-Cited by-同舟云学术

A Data-driven Latent Semantic Analysis for Automatic Text Summarization using LDA Topic Modelling

Published:2022-12-17 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Big Data (Big Data)
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Author:

Onah Daniel F. O.¹,Pang Elaine L. L.²,El-Haj Mahmoud³

Affiliation:

1. University College London,Department of Information Studies,London,United Kingdom

2. Brunel University London,Academic Skills Development,London,United Kingdom

3. Lancaster University,School of Computing and Communications,Lancaster,United Kingdom

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10020192/10020156/10020259.pdf?arnumber=10020259

Reference36 articles.

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2. Literature review of automatic single document text summarization using nlp;haque;International Journal of Innovation and Applied Studies,2013

3. Joint abstractive and extractive method for long financial document summarization;zmandar;Proceedings of the 3rd Financial Narrative Processing Workshop,2021

4. Automatic Text Summarization: A State-of-the-Art Review

5. A survey on abstractive text summarization

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